production access for ai, secured.
intercept, review, and approve destructive ai agent actions before they hit your systems. agents move fast — agent.shield makes sure a human is in the loop for anything that can't be undone.
free to start · no agent rewrite · point a url and you're live.
dashboard
pending
3
approved
128
denied
14
intercepted
1.4k
pending approvals
DELETE /v1/customers/8821
prod database agent · drop record
POST /query
prod database agent · drop table
DELETE /k8s/pods/web-7f
prod database agent · kubectl delete
the problem
one wrong call and prod is gone.
ai agents are getting hands-on with real infrastructure — databases, kubernetes, cloud apis. most of the time that's magic. but a hallucinated DELETE, a stray drop table, or a confident rm -rf doesn't come with an undo button.
- agents act faster than any human can catch in the moment.
- destructive calls look identical to safe ones until it's too late.
- when something breaks, nobody can say who approved what, or when.
the solution
a firewall that asks first.
agent.shield sits between your agent and production as a proxy. safe requests pass straight through. destructive ones are held, surfaced for a human, and only forwarded once someone approves — with a full audit trail either way.
intercept
every request, in-line
review
humans approve or deny
log
who, what, when
what you get
three jobs, done well.
catch destructive actions in-line
point your agent at a agent.shield proxy url instead of your real endpoint. a policy engine inspects every method, path, and payload — matching the patterns that actually hurt: http deletes, drop table, truncate, rm -rf, kubectl delete, and anything you add. safe traffic is forwarded untouched.
- regex policies on method, path, and request body
- sensible destructive-action defaults out of the box
- zero agent changes — it's just a url swap
DELETE /v1/customers/8821
pendingheld — destructive action awaiting your decision
matched policy “http delete”
host: api.internal.acme.com
authorization: bearer ••••••••
{ "cascade": true }
a person decides what runs
every held request lands in a clean review queue. see the exact method, headers, and body the agent wanted to send, the policy it tripped, and where it would go. approve to forward it to your real system, or deny to stop it cold — one click, fully in your control.
- pending queue with live badge counts
- full request payload inspection before you decide
- approve forwards it for real; deny blocks it
DELETE /v1/customers/8821
pendingheld — destructive action awaiting your decision
matched policy “http delete”
host: api.internal.acme.com
authorization: bearer ••••••••
{ "cascade": true }
an audit trail you can trust
nothing happens off the record. agent.shield logs every intercepted request, its payload, the matched policy, and the human decision — who approved or denied it and exactly when. when an incident review asks 'how did this happen?', you have the answer.
- immutable record of every request and decision
- reviewer identity and timestamp on every action
- filter and search across all agent activity
dashboard
pending
3
approved
128
denied
14
intercepted
1.4k
pending approvals
DELETE /v1/customers/8821
prod database agent · drop record
POST /query
prod database agent · drop table
DELETE /k8s/pods/web-7f
prod database agent · kubectl delete
the cost of an un-reviewed agent.
ibm puts the global average cost of a data breach at $4.88 millionin 2024 — the highest on record. as agents take real actions on real systems, a single un-reviewed destructive call is no longer a hypothetical. agent.shield turns "hope it doesn't" into "it can't without us."
$4.88m
avg breach cost (ibm, 2024)
1 url
to get protected
100%
actions logged
do i have to change my agent's code?+
no. agent.shield is a transparent http proxy. you swap the endpoint your agent calls for the proxy url we generate. everything else — auth headers, payloads, methods — passes through exactly as before.
what counts as a destructive action?+
whatever your policies say. out of the box we hold http deletes and bodies containing patterns like drop table, truncate, delete from, rm -rf, and kubectl delete. you can add or remove rules per proxy using simple method + path + body regex matching.
what happens to a request while it waits for approval?+
it's held. the agent receives a 202 response telling it the action is pending human review, along with a link to the review screen. once you approve, agent.shield forwards the original request to your real system and returns the result. deny, and it never runs.
is everything logged?+
yes. every intercepted request, its full payload, the matched policy, and the approve/deny decision — with reviewer and timestamp — is recorded. safe forwarded traffic is logged too, so you have one place to see all agent activity.
who is this for?+
sre, devops, security engineers, and ai developers shipping agents against production systems. if an agent can touch something you can't afford to lose, agent.shield is the seatbelt.
put a human back in the loop.
spin up your first proxy in minutes. no agent rewrite, no new sdk — just a url your agent already knows how to call.