AI & Agents
AgentGuard
Last updated 2026-07-24 · benchmark measured 2026-10-06 — deterministic & reproducible
AgentGuard is a mission-aware firewall that monitors and controls autonomous AI agent actions.
AgentGuard at a glance
AgentGuard is a mission-aware firewall that sits between an AI agent and the actions it can take—payments, email, data exports, API calls, and shell commands—judging each one against the agent's declared mission, for AI agent builders, enterprise security teams, autonomous systems operators, and AI safety engineers.
Good for
- Catching prompt-injection or agent-hijacking attacks where an action passes all numeric policy rules but doesn't match the agent's stated mission
- Requiring human approval or auto-blocking high-risk agent actions above a set confidence threshold
- Keeping a tamper-evident, hash-chained audit record of every decision an AI agent's actions go through
Questions people ask
What does AgentGuard actually check before an agent acts?
It runs every proposed action through a deterministic policy floor (caps, allowlists, integer cents) and a GPT-5.6 intent layer that compares the action to the agent's declared mission; both checks must pass.
Can AgentGuard catch attacks that pass all the normal rules?
Yes, it is designed to catch prompt-injection and agent-hijacking attacks that stay within numeric limits (like spend caps and allowlists) but fall outside the agent's stated purpose.
What happens if the GPT-5.6 intent layer is unavailable?
The system fails closed, meaning actions are not allowed through if the intent-judging model can't be reached.
What happens to suspicious actions?
Actions above a set confidence threshold are held for human approval or automatically blocked, depending on the threshold crossed (0.80+ for approval, 0.95+ for auto-block).
Does AgentGuard replace existing spend controls or agent wallets?
No, it does not hold funds or replace spend controls; it is described as composing with deterministic controls like spend caps rather than competing with them.
Written by Legit.Show from agentguard-dusky.vercel.app on 2026-10-24. It does not change the score.
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To cite this score: legit.show/s/agentguard-dusky-vercel-app/2026-10-06. That address never changes; this page moves with every re-measure.
Legit.Show scored AgentGuard 76/100 on 2026-10-06, measured across all 7 frames from its public surface. legit.show/s/agentguard-dusky-vercel-app/2026-10-06
Is AgentGuard production-ready?
Legit.Show scores AgentGuard 76 out of 100 — the simple average of its 7 measured frames. Legit.Show ran its deterministic 7-Frame production-readiness benchmark on AgentGuard (public-surface assessment), measured from the public surface with no LLM in the scoring path. Its strongest frame is Accessibility; its weakest is Privacy. Every frame it averages is published with its evidence on the Legit.Show listing.
The 7 Frames
- Performance — 99/100
- Accessibility — 100/100
- Security — 45/100How this compares across the catalogue: The Web Security Baseline
- Privacy — 25/100How this compares across the catalogue: The Privacy Gap
- Reliability — 100/100
- Standards — 89/100
- Discoverability — 75/100
What we measured
- Security headers present: HSTS.
- No Content-Security-Policy.
- Served over HTTPS with a valid certificate.
- Real Lighthouse performance run — 290 ms to first byte.
- Returns a proper 404 for unknown routes.
- 1 of 1 sampled routes reachable.
- No privacy policy found.
- Sets cookies / loads scripts with no consent prompt.
Who it's for
AI agent builders · Enterprise security teams · Autonomous systems operators · AI safety engineers
Sources and updates
- Description
- Taken from agentguard-dusky.vercel.app's own website on 2026-07-24.
- Benchmark
- Measured by Legit.Show from the live site, the way any visitor sees it — with no access to its code or accounts. Same method for every product, and no AI decides the score. Last checked 2026-10-06.
Put together from public information, without AgentGuard's involvement. If anything here is wrong, tell us and a person will check it.
Visit AgentGuard → · Alternatives to AgentGuard → · How this was measured →