OWASP

Audit AI agent configurations for security risks — excessive permissions, prompt injection surfaces, data exfiltration paths, and missing guardrails. Use when reviewing CLAUDE.md files, MCP configs, agent orchestration code, or any AI agent setup.

Assess agentic AI applications against the OWASP Top 10 for Agentic Applications 2026. Use when reviewing autonomous AI agents, multi-agent systems, or agentic workflows for security risks including goal hijacking, tool misuse, privilege abuse, and rogue agent behavior.

Comprehensive LLM security assessment against OWASP Top 10 for LLM Applications 2025. Use when reviewing LLM-integrated applications, RAG pipelines, chatbots, AI agents, or GenAI features. Covers prompt injection, data poisoning, supply chain, excessive agency, and more with real-world attack scenarios and testing methodologies.

Security review of MCP (Model Context Protocol) server implementations and configurations. Use when auditing MCP server source code, evaluating third-party MCP servers before installation, or reviewing Claude Code MCP integrations for overpermissioning, injection risks, and data exposure.

Test LLM-integrated applications against known prompt injection techniques, evasion methods, and attack intents using the Arcanum PI Taxonomy. Use when red-teaming AI apps, validating guardrails, or deepening LLM01 (Prompt Injection) assessments.

Comprehensive API security review against OWASP API Security Top 10 (2023). Use when reviewing OpenAPI/Swagger specs, auditing REST/GraphQL/gRPC implementations, testing authentication mechanisms, or checking API gateway configurations. Covers BOLA/IDOR, broken auth, mass assignment, rate limiting, SSRF, and more with real-world attack scenarios.

Security-focused code review mapped to OWASP Top 10 and ASVS. Use when reviewing pull requests, auditing files or modules for vulnerabilities, or performing pre-merge security gate checks. Covers injection, auth, authorization, cryptography, data exposure, misconfiguration, and deserialization.

Security review of Infrastructure-as-Code (Terraform, Kubernetes, CloudFormation). Use when reviewing IaC files for misconfigurations, overpermissioning, exposed resources, missing encryption, secrets in code, and supply chain risks. Covers CIS benchmarks and cloud security best practices.

Assign real MASTG IDs to draft files that use fake placeholder IDs (e.g. MASTG-KNOW-0x01, MASTG-BEST-0x56). Use when finishing a PR that introduces new MASTG components with placeholder IDs, or when asked to "fix fake IDs", "assign real IDs", or "use next available IDs". Runs next_id.py to get the correct next IDs, renames all affected files, and replaces all in-content references.