AI SECURITY RESEARCH · PRACTITIONER GUIDANCE
Published research, incident analysis, regulatory context and practitioner guidance. Each article should be read with its stated sources, scope and limits.
Open to read · Publication counts below reflect the published records currently available on this site.
Check the publication ID and date, the source basis, the claim being made and its limits. A published article does not by itself establish an assessment, certification or finding about a particular system. Corrections should remain visible and point to the current authoritative version.
PUBLICATIONS
The catalog includes the published WordPress records available on this site. Search matches titles, article text, publication IDs, tags and recorded evidence-basis fields. Category and year narrow the results; sort changes their order. A match is a retrieval result, not an endorsement or evidence-tier judgment.
ODA3-2026-07-INS-078
A source-bounded research report on how modern AI interoperability protocols shift enterprise trust boundaries into identity, authorization, extension governance, operational state, and evidence.
Read publication →ODA3-2026-07-INS-077
A source-bounded incident analysis of OpenAI's disclosed model-evaluation escape, the Hugging Face production impact, and the assurance-boundary lessons for AI evaluation environments.
Read publication →ODA3-2026-07-INS-074
AI Investigation Readiness: Governing, Operating and Validating AI-Assisted Investigative Capability
Read publication →ODA3-2026-07-INS-075
A founder note on why ODA3 Institute published the GAISSF Ecosystem for operational AI security assurance.
Read publication →ODA3-2026-07-INS-076
ODA3 Institute has published the GAISSF Ecosystem, connecting AI governance controls, incident classification, and response readiness through GAISSF™, UAIF™, and AI-IRF™.
Read publication →ODA3-2026-07-INS-072
The high-risk deadline moved. The operational incident-response questions remain.
Read publication →ODA3-2026-07-INS-073
The timetable changed. Operational evidence still has to work.
Read publication →ODA3-2026-07-INS-071
A public-disclosure analysis of the reported Hugging Face intrusion, separating confirmed pipeline compromise from unresolved claims about autonomous attack behavior.
Read publication →ODA3-2026-07-CHT-SEC-010
Governance becomes operational when ownership, decision rights, lifecycle gates, incident authority and evidence requirements can be applied to a real AI system.
Read publication →ODA3-2026-07-CHT-SEC-011
Generic incident-response plans assume deterministic software and a single rollback target. AI systems introduce model, prompt, retrieval, agent, credential and evidence states that must be contained and recovered together.
Read publication →ODA3-2026-07-CHT-SEC-012
Vector databases behind retrieval-augmented generation systems can hold sensitive source text and embeddings. Secure them across ingestion, storage, query-time authorization, monitoring and deletion.
Read publication →ODA3-2026-07-CHT-SEC-013
Retrieval-augmented generation creates a security boundary across sources, ingestion, retrieval, context, generation and downstream action. Protecting only the model or vector database leaves the rest of that boundary exposed.
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