Evasive shellcode loader for bypassing event-based injection detection (PoC)
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Updated
Aug 23, 2021 - C++
Evasive shellcode loader for bypassing event-based injection detection (PoC)
A Python library for Secure and Explainable Machine Learning
Phantom-Evasion-Loader is a standalone, pure x64 Assembly injection engine engineered to minimize the detection surface of modern EDR/XDR solutions and Kernel-level monitors like Falco (eBPF). It leverages advanced techniques such as SROP and Zero-Copy Injection to deliver payloads as a ghost in the machine.
The repository is dedicated to Evasion Generative Adversarial Network source code.
📄 [Talk] OFFZONE 2022 / ODS Data Halloween 2022: Black-box attacks on ML models + with use of open-source tools
Taller de Adversarial Machine Learning
Adversarial Malware Generator - A reinforcement learning framework for generating adversarial malware samples to evade GBDT-based and other malware classifiers.
SE4AI Project - Evasion Attacks on Self-Driving Cars to find vulnerabilities
Mostly malicious or abusable powershell I've written
Evaluating adversarial machine learning attacks in network intrusion detection systems.
A learning-focused simulation of adversarial attacks against ML-based network intrusion detection systems within a Zero-Trust architecture, including constrained adversarial modeling, policy enforcement, and security-focused evaluation metrics.
Testing adversarial ML attacks (data poisoning, targeted misclassification, and model extraction) and discussing defensive tradeoffs that exist for real deployments.
Adversarial evasion attacks with constraint satisfaction guarantees.
POC developed while writing the paper "A weakness in eBPF-based runtime security applications"
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