
RAGSieve
Self-referenced local contrast for knowledge-poison detection in retrieval-augmented generation

Self-referenced local contrast for knowledge-poison detection in retrieval-augmented generation
ThreatSentry AI is an intelligent threat hunting dashboard that leverages machine learning to proactively identify and prioritize risks in your…

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

Sec-Gemini is a cutting-edge AI model designed to enhance cybersecurity capabilities and empower defenders in the ongoing battle against cyber…

Asymmetric defense against adversarial AI agents. VeilGate evaluates each incoming request, redirects suspected agents into a per-IP-consistent…

ML-based detection of Zombie ZIP archive header evasion attacks (CVE-2026-0866)

Protection against Model Serialization Attacks

First iteration of ML based Feedback WAF

Website defacement attack detection with deep learning

Reverse Shell Detection with Machine Learning

Analyzes LLM internal states and 100+ attention/probability features to train classifiers that detect document poisoning attacks in RAG systems.

A Red Team vs. Blue Team Adversarial AI Simulation.

AIEngine is a next generation interactive/programmable Python/Ruby/Java/Lua and Go NIDS (Network intrusion detection system).

Graph-based insider threat detection using GCN-BiLSTM and attention models on CMU CERT datasets. Includes data preprocessing, feature extraction, and…

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

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

A machine learning toolkit for log-based anomaly detection [ISSRE'16]

List of tools & datasets for anomaly detection on time-series data.