AI Agent Security

Protect agentic AI systems from adversarial input, unsafe tool execution, data leakage, and privilege abuse with layered security controls.

These are partial design sketches, not a working security boundary. Regexes/classifiers have false positives and false negatives; prompt text cannot grant permissions. Enforce tenant identity, resource scope and approved actions in the tool service using authenticated server-side context. Input signing authenticates origin, not the safety of signed content. Bind approvals to the exact operation/arguments and recheck immediately before execution. Test failure paths and concurrency before production use.

Prerequisites

• Python 3.10+ for guardrail code examples
• Docker or Podman for sandbox execution
• OpenTelemetry collector for audit logging
• Familiarity with your agent framework (LangChain, CrewAI, Autogen, custom)
• Access to policy engine (OPA/Cedar) for permission boundaries

Threat Model — STRIDE for AI Agents

AI agents introduce a unique threat surface. Apply STRIDE specifically to agentic components: