AI Agent Security Review Before Production

An AI agent security review is a pre-launch pass that checks what the agent can read, what it can change, which tools can cause external effects, and how it handles untrusted content.

Quick Answer

1. Inventory every tool and permission.
2. Test indirect prompt injection across each content source.
3. Require confirmation for external sends and destructive writes.
4. Log tool calls with actor, input, output, and target.
5. Add regression tests for every failed attack.

Start with capabilities

Security starts with the tool list. An agent that can only summarize public pages has a different risk profile than one that can email customers, move calendar events, or spend money.

Write down the read surfaces, write surfaces, external-send paths, and secrets the agent can touch.

Test untrusted content

Put hostile instructions in emails, pages, docs, tickets, and retrieved chunks. Then ask the agent to do normal work. The test is whether it treats the hostile text as data or as an instruction.

Confirm risky actions

External sends, payments, deletions, permission changes, and bulk edits should require human approval or a narrow policy gate.

Where BreakMyAgent fits

BreakMyAgent turns the review into repeatable test cases, so teams can rerun the suite after prompt, model, or tool changes.

FAQ

Is prompt injection the only risk?

No. Tool scope, missing logs, overbroad permissions, and weak confirmation flows matter just as much.

Should every agent have the same review?

No. Match the review to the agent's permissions and external effects.

What should fail closed?

External sends, destructive writes, money movement, and secret access.