
Detection-struts-cve-2017-5638-detector
Real-time anomaly detection system for Apache Struts CVE-2017-5638 exploit using streaming analytics, 3-gram byte analysis, and Count-Min Sketch.…

Real-time anomaly detection system for Apache Struts CVE-2017-5638 exploit using streaming analytics, 3-gram byte analysis, and Count-Min Sketch.…

An automated, high-precision zero-shot evaluation pipeline for OpenAI's CLIP model on CIFAR-10. Features 88.80% accuracy, Safetensors security…

Machine learning-based exploit for CVE-2023-1177 vulnerability, enabling automated security testing and exploitation of the identified flaw.

0-day malware detection for binaries, source & scripts (that doesn't suck)

Experiments for control-token chain-of-thought suppression and parser-leniency attacks on tool-using LLM agents

Multi-layered prompt injection detector for AI applications using heuristics, LLM-based analysis, vectorDB attack signatures, and canary token leak…

This project contains the source code for the CERT Basic Fuzzing Framework (BFF) and the CERT Failure Observation Engine (FOE).

Adversarial image perturbation tool that uses SAM segmentation and CLIP models to evade AI-based scam image classifiers for security research.

Fully automatic censorship removal for language models

Test your prompts, agents, and RAGs. Red teaming/pentesting/vulnerability scanning for AI. Compare performance of GPT, Claude, Gemini, DeepSeek, and…

Modular LLM vulnerability scanner that probes for hallucination, data leakage, prompt injection, jailbreaks, and toxicity using static, dynamic, and…

A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine…

Open-source framework for red-teaming generative AI systems: automate attack prompts, score model responses, and audit behavior to identify security…

🐢 Open-Source Evaluation & Testing library for LLM Agents

Streaming machine learning library for incremental learning on data streams, providing online estimators, drift and anomaly detection, pipelines,…

The community's most comprehensive, continuously-updated index of research on Large Language Models for software vulnerability detection — papers…

Interactive dashboards and libraries for responsible AI model debugging, covering error analysis, fairness, interpretability, counterfactuals, causal…

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in…