
sentrygrid
ML-driven threat detection and continuous monitoring platform built for federal zero trust architectures.

ML-driven threat detection and continuous monitoring platform built for federal zero trust architectures.
🐢 Open-Source Evaluation & Testing library for LLM Agents

AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning

Serverless AWS security automation framework that ingests threat intelligence, applies ML-based anomaly detection (RCF, IP Insights), and enriches…

Benchmark and evaluation harness testing whether LLM agents resist malicious instructions hidden in multimodal skill images, with 108 cases across…

Customer Assurance Operating System. Answer the security questionnaires your customers send you, once.

Privacy testing library for deep learning systems, enabling assessment of susceptibility to membership inference, model extraction, and model…

C-based Android static analysis framework for decompilation, secret detection, endpoint discovery, permission analysis, and native library scanning…

Adversary-resilient deep learning architecture for secure 5G indoor localization, combining CNN and multi-head attention to defend against signal…

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

Droidefense: Advance Android Malware Analysis Framework

Open-source OCR engine with LSTM neural network models for extracting text from images and scanned documents in 100+ languages via CLI, C/C++…

Deep learning framework for object detection, segmentation, classification, pose estimation, and tracking using pre-trained YOLO models and…

NVR with realtime local object detection for IP cameras

Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

Open Source Deep Packet Inspection Software Toolkit

Defeating Google's audio reCaptcha with 85% accuracy.

🥂 Gracefully face hCaptcha challenge with multimodal large language model.