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adversarial-ml

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depalmar / ai_for_the_win

Star 149

Build AI-powered security tools. 50+ hands-on labs covering ML, LLMs, RAG, threat detection, DFIR, and red teaming. Includes Colab notebooks, Docker environment, and CTF challenges.

python docker machine-learning ai incident-response dfir cybersecurity ctf threat-hunting xdr siem malware-analysis security-training threat-intelligence cloud-security blue-team threat-detection hands-on-labs adversarial-ml llm
  • Updated Jun 1, 2026
  • Python

AmirhosseinHonardoust / Noise-Injection-Techniques

Star 22

Noise Injection Techniques provides a comprehensive exploration of methods to make machine learning models more robust to real-world bad data. This repository explains and demonstrates Gaussian noise, dropout, mixup, masking, adversarial noise, and label smoothing, with intuitive explanations, theory, and practical code examples.

data-science machine-learning deep-learning tabular-data pytorch dropout neural-networks regularization data-augmentation data-quality noise-injection label-smoothing mixup ai-research gaussian-noise ml-engineering model-robustness adversarial-ml ml-theory ml-robustness
  • Updated Nov 15, 2025

AI-Security-Research-Group / LLM-Attacks

Star 17

Comprehensive taxonomy of AI security vulnerabilities, LLM adversarial attacks, prompt injection techniques, and machine learning security research. Covers 71+ attack vectors including model poisoning, agentic AI exploits, and privacy breaches.

machine-learning ai-security ai-privacy open-source-security adversarial-ml prompt-injection ai-red-teaming model-poisoning llm-attacks ai-vulnerabilities security-taxonomy
  • Updated Sep 19, 2025

MadsDoodle / Detecting-the-Machine-A-Comprehensive-Benchmark-of-AI-Generated-Text-Detectors-Across-Architectures

Star 7

This project aims to address this gap by conducting a systematic, controlled study of human versus LLM-generated text detectability using paired question–answer datasets. Rather than proposing a novel detection architecture, the focus is on analyzing detection robustness, failure modes, and the impact of adversarial humanization strategies.

nlp benchmarking text-classification transformers xgboost stylometry bert model-evaluation electra perplexity roberta domain-generalization adversarial-ml ai-evaluation llm-detection ai-generated-text-detection llm-benchmarks
  • Updated Mar 19, 2026
  • Jupyter Notebook

issdandavis / SCBE-AETHERMOORE

Sponsor
Star 6

Geometric AI governance and evaluation framework with a 14-layer security pipeline, semantic projection, and reproducible benchmark lanes.

machine-learning cryptography post-quantum-cryptography hyperbolic-geometry multi-agent-systems autonomous-agents ai-safety security-framework ai-alignment adversarial-ml ai-governance poincare-ball ai-red-team prompt-injection llm-security patent-pending ai-firewall runtime-governance sacred-tongues geometric-security
  • Updated Jun 19, 2026
  • Python

zakky8 / llm-jailbreak-taxonomy

Star 3

Mechanism-grounded taxonomy of 40 LLM jailbreak patterns across 10 categories. 8,000-trial bootstrap evaluation for the June 2026 frontier (Claude Opus 4-8, GPT-5.5, Gemini 3.5, DeepSeek V4). Every citation direct-WebFetch verified; refuted claims documented.

taxonomy jailbreak alignment ai-safety security-testing responsible-disclosure jailbreak-detection adversarial-attacks red-teaming ai-security model-robustness adversarial-ml prompt-injection red-teaming-tools llm-security llm-evaluation llm-jailbreaks ai-red-teaming adversarial-testing
  • Updated Jun 2, 2026
  • Jupyter Notebook

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