mortar
adversarial-robustness-toolbox
| mortar | adversarial-robustness-toolbox | |
|---|---|---|
| 3 | 8 | |
| 1,348 | 4,460 | |
| 1.0% | 1.2% | |
| 5.7 | 9.7 | |
| 4 months ago | 10 days ago | |
| Pascal | Python | |
| MIT License | MIT License |
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mortar
- Mortar Loader: evasion technique to defeat and divert detection and prevention of security products (AV/EDR/XDR) - Mortar Loader performs encryption and decryption of selected binary inside the memory streams and execute it directly with out writing any malicious indicator into the hard-drive
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mortar: evasion technique to defeat and divert detection and prevention of security products (AV/EDR/XDR)
it is now fixed, it was an issue with the encryptor.https://github.com/0xsp-SRD/mortar/issues/1
adversarial-robustness-toolbox
- [D] Couldn't devs of major GPTs have added an invisible but detectable watermark in the models?
- [D] ML Researchers/Engineers in Industry: Why don't companies use open source models more often?
- [D]: How safe is it to just use a strangers Model?
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[D] Does anyone care about adversarial attacks anymore?
Check out this project https://github.com/Trusted-AI/adversarial-robustness-toolbox
- adversarial-robustness-toolbox: Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
- Library for Machine Learning Security Evasion, Poisoning, Extraction, Inference
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Introduction to Adversarial Machine Learning
Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to defend and evaluate Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference.
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[D] Testing a model's robustness to adversarial attacks
Depending on what attacks you want I've found both https://github.com/cleverhans-lab/cleverhans and https://github.com/Trusted-AI/adversarial-robustness-toolbox to be useful.
What are some alternatives?
DefenderCheck - Identifies the bytes that Microsoft Defender flags on.
DeepRobust - A pytorch adversarial library for attack and defense methods on images and graphs
TelemetrySourcerer - Enumerate and disable common sources of telemetry used by AV/EDR.
auto-attack - Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
Veil - Veil 3.1.X (Check version info in Veil at runtime)
TextAttack - TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
URL-obfuscator - Python Program to obfuscate URLs to make Phishing attacks more difficult to detect. Uses Active open redirect list and other URL obfuscation techniques.
alpha-zero-boosted - A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)
Payload-Download-Cradles - This are different types of download cradles which should be an inspiration to play and create new download cradles to bypass AV/EPP/EDR in context of download cradle detections.
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
waf-bypass - Check your WAF before an attacker does
Differential-Privacy-Guide - Differential Privacy Guide