Skill UI

A comprehensive guide detailing advanced security threats in Machine Learning and AI systems. Covers model supply chain attacks (RCE via pickle, poisoning), adversarial examples (FGSM, PGD, physical-world), data privacy breaches, and LLM-specific vulnerabilities. Essential for building robust, secure AI pipelines.

This comprehensive playbook details advanced techniques for testing and exploiting Large Language Models (LLMs). It covers direct instruction override, indirect poisoning via RAG and web sources, function/tool abuse, and sophisticated data exfiltration methods. Essential reading for AI security researchers and penetration testers.

A rigorous, Chief AI Officer-level interrogation tool designed to pressure-test any plan involving artificial intelligence. Before deployment, it forces comprehensive review across crucial dimensions: evaluation metrics, hallucination risk, EU AI Act compliance, model architecture selection (API vs. build), cost economics, and required organizational roles. Essential for maintaining AI product safety and compliance.

A comprehensive compliance operator designed to pressure-test any AI system against the stringent requirements of the EU AI Act. Before deployment in the European Union, systems must pass six critical checks covering prohibited practices, high-risk classification, conformity assessment modules (A/H), role obligations, transparency mandates, and systemic risk assessment for GPAI.