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AIUC-1 grades the platform. Something still has to read the output.

AIUC-1 is becoming the SOC 2 for AI agents. One of its mandatory coding-agent requirements, A008, asks for scanning logic applied to generated files and block or flag logic on any secrets it finds. That is a scan of the output an agent ships.

GRC platforms automate the evidence and the policy that get you to the certificate. Seatbelt runs the scan and hands you the report.

01An accredited auditorSchellman and peers audit for the certificate.Covered
02A GRC platformDrata and Vanta collect evidence and map controls.Covered
03A scanner that reads the generated appFor the requirements that are about the output. A008 asks for scanning logic, so something has to run it.The gap

The code an agent ships is where the risk lands.

A008 names post-generation scanning of output files for common credential patterns as a safeguard, and its evidence spec asks you to show the scanning logic and the block or flag behavior. Those are properties of the code, provable only by reading it.

10.5%
of AI-generated code passes security review, even though 61% of it runs correctly.OX Security, 2026
~20%
of packages an AI recommends do not exist, a ready-made supply-chain target.USENIX Security, 576k samples
A008.2
asks for “scanning logic applied to generated files” and “block/flag logic preventing persistence of outputs containing detected secrets.” That is a scanner, written into the evidence spec.AIUC-1 A008, released 2026-07-15

The output-scanning layer, next to your compliance program.

Seatbelt reads an AI-generated application across six surfaces and returns a Ship Read: what is exposed, what is unguarded, what is safe. It is not a replacement for your GRC platform or your auditor. It is the piece that reads the generated code, and the report attaches as evidence for the output controls.

Auditorowns the certificate.
GRC platformowns evidence and policy.
Seatbeltowns the read of the generated code.

Six surfaces, mapped honestly to the requirements about the code.

One surface is a strong fit for a requirement. Several are partial. One maps to nothing, and the row says so rather than reaching for an ID.

SurfaceWhat Seatbelt readsAIUC-1 requirement
SecretsHardcoded API keys, tokens, and credentials in generated codeA008Prevent leakage of credentials and secrets (strong fit)
Customer dataEndpoints returning data not scoped to the requester; PII in responses and logsA006Prevent PII leakage (partial)
DatabasesQuery construction open to injection; unsafe ORM useC006Prevent output vulnerabilities (partial)
LoginAuthorization on the page but not the action behind it; weak session and cookie defaultsNo requirement claimed. The standard covers auth defaults at generation time, not at read time. We read this surface because it is a ship killer, not because a control names it.
PaymentsMoney paths and data handling that skip validationA006Prevent PII leakage (partial)
Risky shortcutsAdmin routes on guessable paths; actions that skip authorization; import strings missing from the nearest package.json manifestC006Prevent output vulnerabilities (partial)D001Prevent hallucinated outputs (phantom-dependency facet, partial)

Requirement IDs are read from the live AIUC-1 standard, released July 15, 2026 and refreshed quarterly (next October 15). That update named coding agents as a focus area. We do not quote a requirement count on this page: published counts disagree, and the July release changed eight more.

One requirement we fit strongly. Three partial. One we do not claim.

A008 is the fit. Its evidence spec asks for scanning logic applied to generated files and block or flag logic on detected secrets, which is what a Ship Read is. C006, A006, and the phantom-dependency facet of D001 are partial, and we say partial because they are. It is not your whole AIUC-1 program. We name the requirements we address, not a percentage of the standard.

  • It does not draft policy, run your governance workflow, or issue the certificate.
  • It does not cover accountability, red-team testing, runtime tool gating, or refusal controls. Those are not scanner-shaped and stay with your auditor, your GRC platform, and your own controls.
  • B010 (not claimed): its six named safeguards are all generation-time defaults, from parameterized queries to pinned dependencies to cookie flags, delivered through system prompts, scaffolding, and configuration. Static analysis is not among them. We read the code after it is written, so this is the agent's requirement, not ours. Earlier versions of this page named it as an evidence source. That was wrong, and we removed it.
  • Coverage within C006 and D001 is still deepening. Where a check is not live yet, the gap runs in our test lane so the catch rate is measured the day the detector lands, not asserted before it.
  • D001 (partial): orphan imports when an import or require names a package absent from the nearest package.json (static manifest read, no network). Opt-in verify_deps adds bounded npm and PyPI registry checks for declared names. Honest limits: phantom names already listed in the manifest still pass static read; registry verify is opt-in and the report stamps whether it ran. This is the phantom-dependency / manifest-drift facet of D001, not full hallucinated-output coverage.

Everything above, cited.

AIUC-1 requirement catalogaiuc-1.com · released Jul 15 2026, refreshed quarterly, next Oct 15Every requirement ID on this page was read from the live standard, not from a summary. We do not quote a requirement count: published counts disagree, and the July release changed eight more.A008, prevent leakage of credentials and secretsaiuc-1.com · mandatory, scope: agents with code-generation capabilitiesNames post-generation scanning of output files for common credential patterns as a safeguard. Evidence spec A008.2 asks for scanning logic applied to generated files, plus block or flag logic on detected secrets.B010, promote secure patterns in generated codeaiuc-1.com · read Jul 2026All six named safeguards are generation-time defaults delivered through system prompts, scaffolding, and configuration. Static analysis is not named. We do not claim it.Setting the standard for agentic developmentAIUC and Lovable whitepaper, May 202675 coding-agent risks; a hallucinated authentication pattern in generated code is a vulnerability that ships to production.Pursuing AIUC-1 with a GRC platformDrata, 2026Evidence automation and control mapping for teams pursuing AIUC-1. The evidence layer Seatbelt feeds, not competes with.Only 10.5% of AI-generated code passes security reviewOX Security, 202661% of generated code runs correctly; a fraction of that clears a security review.Schellman, first accredited AIUC-1 auditorGlobeNewswire, Feb 2026Thousands of adversarial scenarios; agent behavior re-tested quarterly.

See where the six surfaces line up with your control set.

Or run a Ship Read on a generated app and see the output evidence it produces.

Seatbelt is independent and is not affiliated with, endorsed by, or certified by AIUC or the AIUC-1 standard. Requirement names and IDs are referenced for interoperability and cited to the live standard. Product and company names are the property of their respective owners.