Agentic AI Secured
Hands-on tested security for AI agents, MCP, and AI coding tools
Agentic AI security is the practice of defending autonomous AI agents, the MCP servers they call, and AI coding tools against attacks like prompt injection and credential leakage. Here, "agent" means an LLM-driven software agent that takes actions, not a real-estate, support, or sales agent.
The threat model
Four attack classes account for most agent compromises. Every guide and tool review on this site maps back to defending one of them.
Prompt injection
Untrusted text hijacks the model into following the attacker’s instructions instead of yours.
Excessive agency
An over-permissioned agent acts autonomously at machine speed once it is manipulated.
Tool & MCP abuse
Poisoned tool descriptions and over-broad scopes turn the tool layer into an attack path.
Credential leakage
Secrets in prompts, tool arguments, or agent memory leak and grant standing access.
Start where you need to
AI security tools we tested
First-hand verdicts on MCP scanners, coding-assistant guardrails, and agent runtime hardeners.
GuidesDevSecOps guides for AI workloads
Hands-on guides for secret hygiene, scoped credentials, and least-privilege agent permissions.
OWASPOWASP LLM Top 10 (2026)
Each LLM risk mapped, risk by risk, to the concrete defensive controls that mitigate it.
ChecklistsAI agent hardening checklists
Numbered, verifiable controls that shrink the blast radius of autonomous agents.
Latest guides
- AI agent guardrail tools compared: open source and commercial options An honest comparison of real LLM guardrail tools, NeMo Guardrails, Guardrails AI, LLM Guard, Lakera Guard, and Prompt Security, based on public documentation, with a verdict table and guidance on choosing one.
- Audit your AI agent setup: a hands-on self-audit walkthrough A practical self-audit for your AI agent: inventory tools, check permissions, gate high-impact actions, test prompt-injection exposure, handle secrets, log tool calls, and vet MCP servers. Includes a numbered walkthrough and a printable checklist.
- Excessive Agency explained: OWASP LLM06 and how to contain it A definition-dense explainer of OWASP LLM06 Excessive Agency: what it means, the three sub-types of functionality, permissions, and autonomy, real examples, and the least-privilege defences that work.
- gitleaks vs TruffleHog: which secret scanner should you use? An accurate, hands-on comparison of gitleaks and TruffleHog: detection approach, live secret verification, scan targets, config, CI and pre-commit support, licences, and an honest verdict on which to pick.
- Prompt injection detection tools compared: 5 real options An honest comparison of real prompt injection detection tools, Rebuff, LLM Guard, Lakera Guard, Prompt Security, and Vigil, covering their detection approach, open-source versus commercial status, and the limits of catching indirect injection.
- What is an AI agent? Definition, how it works, and why it is a security risk A clear definition of an AI agent: software that uses an LLM to plan and call tools autonomously. Covers how it works, AI agent vs chatbot vs LLM, examples, and why agents are a security concern.