KIMURA
AI AGENT BOUNDARY VERIFICATION
Prove your AI agent stays inside its action boundaries.
A policy says what an agent should do. Kimura verifies both sides of the action boundary using controlled allowed/forbidden tests, observable outcomes, deterministic verdicts, and exact remediation replay.
BLACK HAT EUROPE 2026 · MULTI-BOUNDARY PROOF6 Benchmark v1.1 familiesAI agents now take consequential actions.
They issue refunds, access tenant resources, invoke privileged actions and send data to external destinations.
A written rule is not proof. The action boundary must be tested on both sides and observed in state.
KIMURA PROOF METHOD
The scenario changes. The proof chain does not.
- 01Executable Action Contract
- 02Controlled Boundary Pair
- 03Actual Attempt
- 04Outcome Oracle
- 05Deterministic Verdict
- 06Exact Remediation Replay
- 07Allowed-Function Preservation
- 08Proof Capsule
ONE ENGINE. DIFFERENT ACTION BOUNDARIES.
Six currently verified families. No unsupported family is presented as current capability.
Financial Authority
Amount, limit and approval scope
Identity Equality
Approved actor versus substituted identity
Tenant / Resource Ownership
Owned resource versus cross-tenant target
Privileged Action
Approved operation versus privileged action
Egress Destination
Approved destination versus unapproved endpoint
Egress Data Classification
Permitted data versus restricted payload
REMEDIATION DOUBLE PROOF
A fix is verified only when the forbidden effect disappears and the legitimate action still works.
PROOF, NOT MODEL OPINION
The model’s explanation is not the source of truth.
Executable policy expectation
Identity, action, arguments and target
Independent state or receipt observation
Kimura derives each canonical verdict from the declared boundary, execution evidence and observed outcome. No LLM judge decides whether the boundary held.
BENCHMARK V1.1
- 91
- compiled clauses
- 26
- supported
- 65
- unsupported
Unsupported clauses remain in the denominator instead of being silently excluded.
EVIDENCE LIMITATIONS
Current public benchmark evidence is synthetic-controlled and harness-observed.
Hash verification establishes artifact integrity and linkage. It does not independently prove the truth of an external production event.
CUSTOMER-PRODUCTION PROOF IS NOT CLAIMED UNLESS CUSTOMER-OWNED EVIDENCE IS PRESENT.WHEN THE AGENT CHANGES, ITS AUTHORITY SHOULD NOT SILENTLY FOLLOW.
AI agents are becoming capable of changing their code, models, tools, connectors, workflows and execution paths.
An approval or security proof established for one agent state should not automatically be assumed valid for the next.
Kimura is researching how to re-resolve what is actually running after a material change, then re-prove whether the approved action boundary still holds.
- 01Approved state
Artifact · Identity · Policy · Credential · Target · Execution path
- 02Mutation
Code · Model · Tool · Connector · Workflow
- 03Re-resolve
Establish what is actually running now
- 04Re-prove
Replay the same allowed and forbidden boundary pair
- 05Authority decision
MUTATION_VERIFIED or GOVERNANCE_CONTINUITY_BROKEN
Mutation may change capability. It must not silently inherit authority.
FROM REFUNDS TO AUTONOMOUS MONEY
- agentic payments
- digital-asset / crypto wallet authority
- smart-account spending policies
- AI-controlled treasury operations
“Is this action allowed?”It is:
“Does the agent performing it still deserve the authority it inherited?”
HAVE AN AI AGENT WITH REAL TOOLS AND ACTION POLICIES?
Kimura is looking for design partners to test boundary verification against real agent systems and customer-owned evidence sources.
- Tool-using AI agent
- Controlled test environment
- Explicit action or authorization policies
- Trusted outcome source
Building AI Agent Boundary Verification for systems where agents can take consequential actions.