Independent Auditing of AI Agents. Run by human or the agent itself, to answer the most crucial question in the AI Agent Economy. Is the agent doing what is supposed to do? With iFixAi you can have this answer in less than 120 seconds.
🐢 Open-Source Evaluation & Testing library for LLM Agents
The Python Risk Identification Tool for generative AI (PyRIT) is an open source framework built to empower security professionals and engineers to proactively identify risks in generative AI systems.
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
A Python package to assess and improve fairness of machine learning models.
A platform-neutral analytical Skill that profiles messy data, selects case-adaptive methods, and produces source-backed visual reports for high-stakes decisions.
A cautious, explainable AI text detector for local workflows and coding agents. Need production detection in your app? Try the Lynote AI Detector API → lynote.ai/ai-detector-api
[ICML 2024] TrustLLM: LLM trustworthiness evaluation across truthfulness, safety, fairness, robustness, privacy and ethics. Python/CLI toolkit for local models, compatible APIs and AI agent orchestration.
开源劳动者AI研究与评测项目:建设劳动知识、公开评测基准与共同治理机制|Open worker-centered AI research and evaluation project.
Policy-aware static taint analysis for detecting sensitive-data flows into LLM APIs.
YOLO11 research prototype for detecting people associated with potentially dangerous objects in public-area imagery, with thesis evidence, reproducibility notes, and responsible-use guidance.
Myrtia — agent-native red teaming for LLMs and AI agents: a deliberating council of attacker models (propose, cross-critique, Borda vote, chairman synthesis), 13 attack strategies, live turn-by-turn UI and ASR analytics. Open-source, built on IBM ARES.