AI AGENT ACTION-CONTROL VERIFICATION

Prove your AI agent is still authorized when conditions change.

Your agent received approval. But is it still authorized when the tool call actually happens? We test one consequential workflow against changing permissions, stale evidence or uncertain execution, and report what can be verified.

$1,000Introductory Action-Control Check · one workflow · two agreed scenarios
Independent technical assuranceDevSecOps agentsCyber-remediation agentsRetained evidence

Fixed scope, staging or synthetic environment. No certification or production deployment.

Evidence-backed checks. Clear limitations.
Start with one real risk

One workflow. Two control transitions. A report you can inspect.

Designed for agent builders, integrators and security teams who need to decide whether a consequential tool action is still authorized. No platform replacement required for scoping.

Example: An agent has approval to update a CRM record. The approval changes while the agent is working. Does the later write stop? What happens if the first write has an uncertain result and the agent retries?
INTRODUCTORY PILOT

Action-Control Check

$1,000 USD · fixed scope
  • One protected action and one agreed test environment
  • Two authority / retry transition scenarios
  • Retained test artifacts when observable
  • Concise findings and a technical review call
Request this check

Target delivery: 2–3 business days after prerequisites are ready, subject to scope confirmation. Complex adapters, fixes and retests are excluded.

The problem

A valid action can become stale while the agent is still working.

Identity, permission or approval may be correct at the start of a workflow and wrong by the time a consequential action executes. EvidenceBound tests whether control follows the changing basis for authority rather than the original decision alone.

Who it is for

Start with agents that can change production or security state.

DevSecOps agents

Build, deploy, configure infrastructure or continue after code, artifact, approval or security state changes.

Cyber-remediation agents

Rotate credentials, change IAM, isolate hosts, modify firewall state or continue after incident conditions change.

The same control problem may apply to infrastructure and other consequential workflows.

What we test

Four control transitions that can invalidate previously valid authority.

Approval change

Can revoked or superseded approval still reach a consequential effect?

Evidence or policy change

When the basis changes, is materially dependent state invalidated while unrelated valid work remains intact?

Uncertain outcome

If a prior consequence may have committed, can the system create another consequence without an authorized recovery decision?

Recovery authority

Does the need to repair, compensate or retry incorrectly create fresh authority?

Claim boundary. Properties outside the tested conditions are reported as unverified rather than promoted into a PASS claim.
How an assessment works

Five steps from scope to evidence-backed findings.

The starter check includes Scope, Challenge, Observe and Report. Retest is a separately scoped option.

ScopeFreeze the consequential workflow and explicit exclusions.
ChallengeApply agreed authority, evidence, policy and outcome changes.
ObserveRetain the inputs, decisions, target contact and effects that can be evidenced.
ReportReturn findings, limitations and remediation priorities.
RetestVerify the agreed remediation under the same bounded conditions.
Public evidence

RAB-1 shows the type of claim EvidenceBound will make — and the boundary around it.

RAB-1 · Runtime Authority Benchmark

RAB-1 reproduced a duplicate-consequence failure under uncertain execution, then demonstrated fail-closed recovery-authority enforcement under frozen test conditions.

12/12 hard gates8/8 frozen scenariosexact-tag reproduced
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Tested on / enforced through NVIDIA OpenShellIndependent EvidenceBound research; not NVIDIA validation or endorsement.
Assessment

See the $1,000 starter check before commissioning broader work.

EvidenceBound is an independent technical assurance practice for consequential AI-agent control, backed by public research and open technical reference implementations.