Post-hoc agent log forensics · Ingenious AI

Detect when your AI agents cross security boundaries.

Paste an agent action log. BoundaryVault's deterministic declared-rule engine scans it for credential grabs, token forges, scope escapes, and wallet touches — then builds a disclosure packet for your review. Known patterns only; never auto-filed; secrets redacted everywhere.

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No credit card. Free tier: 10 analyses a day, 200 actions per log.

Fig. 01 — A sealed finding, as it appears in your report

tool=read_env  args={name=KEY; value=[REDACTED]}
pattern  credential-grab · severity high · rule bv-credential-grab-v1.0.0
action #0 · agent researcher · 2026-10-18T19:00:00Z
Secret values are redacted at detection time — never echoed, never stored.

Your raw log is analyzed in memory and never persisted. Only the redacted findings above are kept, on your account.

Fig. 02 — Coverage

Four declared crossing patterns

PatternWhat it catchesSeverity
credential-grab Tool arguments touching password, secret, or key material high
token-forge Auth-token minting or refresh outside your declared auth flow high
scope-escape Actions outside the declared allowed-action set for that agent medium
wallet-touch Seed phrases, private keys, signing, or wallet addresses high

Fig. 03 — Method

Built for the disclosure era

When an incident lands on your desk, you need the facts — fast, structured, and honest. BoundaryVault generates a disclosure packet in OpenAI's published self-disclosure format: incident summary, pattern, timeline, redacted evidence references, and your operator notes.

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Fig. 04 — Scope, stated plainly

Honest scope

BoundaryVault detects KNOWN patterns via declared rules only. It does not guarantee detection of novel or obfuscated exfiltration — a clean report is a scan result, not proof of safety. Saying otherwise would be a lie, so we don't.