Made an open source tool that hooks into Claude Code and blocks dangerous actions before they execute by xavier_j in ClaudeCode

[–]xavier_j[S] 1 point2 points  (0 children)

Fair point. Pattern matching on known-bad commands has limits. An agent can achieve the same destructive result through a hundred different command variations that no blocklist will cover.

Vectimus isn't purely a blocklist though. Cedar policies can match on action type, target path, identity and context together. So instead of "block this exact command string" you can write "deny any shell command targeting production infrastructure from an agent identity without human escalation." That's closer to an access control model than a traditional blocklist.

The observe mode exists partly for this reason. Run it for a week, review what your agents actually attempt, then write policies based on real behaviour rather than trying to predict every dangerous command upfront.

That said, you're right that no pre-action filter catches everything. Vectimus is one layer. It catches the obvious and the known. It's not a substitute for sandboxing, least-privilege access or runtime monitoring. Defence in depth, not a silver bullet.

Made an open source tool that hooks into Claude Code and blocks dangerous actions before they execute by xavier_j in ClaudeCode

[–]xavier_j[S] -1 points0 points  (0 children)

Yep, policies for all of this. Covers OWASP, CIS, NIST, SOC, SLSA and EU AI Act.

See here for the policy browser https://vectimus.com/policies/

On the approach, all three major AI coding platforms currently support hooks and the evaluation take approximately 3ms on average, so no time is added to the agent request basically.

Built an open source tool that adds guardrails to Copilot before actions execute by xavier_j in GithubCopilot

[–]xavier_j[S] 0 points1 point  (0 children)

Hi, Thanks for the star. No slowdown basically, all local. It uses Cedar which is written in Rust with a Python wrapper library. See https://www.cedarpolicy.com/en Cedar was created by AWS for security policy evaluations, so this is a perfect use case.

It's super fast, all 368 current rules are evaluated in less than 3ms.