All agents

AI agents for security

3 tools · listed in dataset order, no ranking

AI agents that test applications you are authorized to assess, verify vulnerabilities, and propose fixes.

What matters here:Validated findings vs raw scanner alertsWhere it runs (local, CI, managed cloud) and what code leaves your environmentAuthorization, scoping, and staging-only testing

How to choose a security tool

Testing running apps vs fixing source code

Strix and Shannon test a running application (Shannon also reads its source code) and report issues they can validate. CodeMender works on source code: it verifies findings and drafts tested patches for developers to review. Many teams will want both kinds of coverage.

Only test what you are authorized to test

Active security testing tools can change application state. Their vendors say to run them only against systems you own or have written permission to test, ideally a staging environment with disposable data.

Budget for model usage and run time

The open-source tools here are bring-your-own-model, so each scan incurs LLM costs, and deep runs can take hours. Managed platforms trade that for seat, per-test, or token-based pricing.

Common questions about security tools

What is an AI security agent?

An AI agent that performs security work such as testing an application you are authorized to assess, validating whether a vulnerability is real, or drafting a fix, rather than only listing potential issues.

Are there open-source AI pentesting tools?

Yes. Strix is Apache-2.0 and Shannon is AGPL-3.0. Both run locally or in CI with your own model provider, and both vendors also offer paid hosted platforms.

Do AI security agents replace human pentesters?

No. Vendors say findings still need human review, and coverage is narrower than a full manual assessment. They are best used for continuous or pre-release checks alongside periodic human-led testing.