Google's Open Knowledge Format (OKF v0.1) is the LLM-wiki pattern this
library guards. Capture a security brief for OKF ingestion as tracked
future work -- NOT shipped scope. The v0.1 core is format-agnostic text;
OKF surfaces beyond the body (YAML frontmatter, resource URLs, cross-link
graph, file path / reserved names, format-level authenticity) are uncovered.
- Coverage claims verified against the code at 5397ba1 (brief section 9): no
YAML parse in src, neutralize defangs but has no reject-gate, no path/graph
logic, disposition machinery exists.
- OKF confirmed real at the format level (Google Cloud, 2026-06-12; spec
GoogleCloudPlatform/knowledge-catalog).
- Design move: an OKF adapter ON TOP of the format-agnostic core; the core
stays text->findings.
- Section 8 lists 8 v0.2 tasks (T1-T8); T8 (surface two OKF residual risks in
README honest-limits) can land independently.
One realistic content sample carrying many vulnerabilities at once, run through
a mock ingestion pipeline (sanitize -> lexicon+entropy+decode-rescan -> output
gate -> disposition); assert every planted vuln is caught and disposition fails
secure. Doubles as the README worked example. Added to build-order step 11 and
the test strategy; tracked as task #11. Inspiration: llm-security/examples/*.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01K8GmKRCdsPjWYAKWsNgeQS
Based on the working, tested Layer B ingestion-gate in ms-ai-architect (2026-07-04):
- A: correct consumer 2 — it fetches authored Learn docs + code samples via the
microsoft-learn MCP, NOT the open Q&A forum / MSDN / Stack Overflow (that claim
was unverified/overstated); low-trust surface is intra-document. Repo/name
reconciled: the consumer is ms-ai-architect, no separate "MS AI Security plugin".
- B: §4.7 — trust tiers WITHIN a document (code sample / localized string vs
authored prose), not only across sources; carriers + critical block in any tier.
- C: §12 — consume the lexicon as pure imported functions, not the llm-security
scan CLI (which under-covers Markdown prose + base64-in-code-block, verified).
- D: §4.6 — fail-secure extends to scanner-unavailable: un-scannable ⇒ BLOCK.
Adds ms-ai-architect as the second reference implementation (output side).
Second target consumer named: MS AI Security plugin, an ingestion
pipeline over Microsoft Learn content that includes user-generated Q&A
(learn.microsoft.com/answers, plus ingested MSDN/Stack Overflow). This
is the high-untrust case where the contract is load-bearing, not
hygiene. New design principle 4.7: disposition scales with source trust
(pinned changelog = WARN; open UGC = quarantine/hard-fail on high
severity). Day-1 rationale: architectural controls are cheap to design
in, expensive to retrofit (consumer 1 is proving that at its A13).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01HPAmFyEVWbwvmSNVdXTu4d
