Skill UI

This guide details how to implement robust, multi-layered Role-Based Access Control (RBAC) for managing LLM API calls to Groq in an enterprise setting. It covers best practices for API key scoping, application-level authorization (model selection, token limits), rate limiting, and detailed spending control mechanisms, ensuring secure and cost-effective usage across multiple teams.

This skill provides a comprehensive framework for security auditing LLM agents that possess external tools (file system access, command execution, network calls). It employs advanced dialogue probing techniques—such as command injection, path traversal, and SSRF attempts—to identify vulnerabilities where the agent might be induced to execute unexpected or malicious code, or access sensitive resources. Essential for red teaming and securing agent functionalities.

An automated framework for continuous, repeatable red-teaming of LLM applications within CI/CD pipelines. It integrates Promptfoo and DeepTeam to test against recognized vulnerabilities like OWASP LLM Top 10, OWASP Agentic, and MITRE ATLAS (e.g., Prompt Injection, Jailbreaks). This ensures that security vulnerabilities do not regress after code or model changes, providing a critical merge-blocking security gate for production LLM apps.

An open-source automation framework for conducting multi-turn, adversarial red-teaming against conversational LLMs. PyRIT simulates real-world attacker behavior using advanced orchestrators (Crescendo, TAP) and scorer feedback loops. It is designed for comprehensive security assessments of AI agents and chatbots, going far beyond single-shot prompt testing to evaluate robustness under gradual or adaptive attacks.

Detailed methods for red-teaming and penetration testing of LLM applications. This skill extracts sensitive system prompts, secrets, and embedded logic using advanced techniques like jailbreaking, encoding tricks, and automated scanners (Garak, Promptfoo), ensuring compliance with OWASP LLM07:2025.

A comprehensive framework for conducting authorized security assessments on Large Language Models (LLMs) and AI agents. It covers critical vulnerabilities including advanced prompt injection (OWASP Top 10), tool abuse, RAG data poisoning, memory manipulation, and system prompt extraction. Ideal for red teaming, security auditing, and ensuring the robustness of AI systems in production environments.