Blog

Analysis on enterprise AI governance, inline policy enforcement, agentic AI security, and regulatory compliance.

Korea AI Basic Act AI Compliance Checklist: Ten Actions Before the Grace Period Closes

South Korea''s AI Basic Act took effect on 22 January 2026 with a one-year grace period on administrative fines that closes on 22 January 2027. This is a working checklist of ten actions for an operator running AI traffic into or out of Korea, covering the high-impact determination, the domestic representative thresholds, prior notification, generative AI labelling, human supervision, and the evidence each action produces. Every item names the artifact an MSIT inspection reads rather than the policy it references.

Compliance & Regulationcomplianceai-governanceauditregulationai-security
Read post →

MITRE ATLAS AI Audit Evidence: The Telemetry That Proves a Technique Fired

MITRE ATLAS reached 16 tactics, 84 techniques, 56 sub-techniques, 32 mitigations, and 42 case studies at version 5.1.0 in November 2025, with agent-focused techniques added in the February 2026 update. A technique is only useful in a review if you can show whether it fired. This walks the evidence artifacts that answer that question for the ATLAS tactics reachable over HTTP AI traffic, and names the tactics where no request-path telemetry helps.

Compliance & Regulationai-securityllm-securityauditforensic-auditai-governance
Read post →

MITRE ATLAS AI Compliance Checklist: Ten Actions Against the Techniques That Reach Your Traffic

MITRE ATLAS carries 16 tactics and 84 techniques as of version 5.1.0 in November 2025, with agent-focused additions landing in February 2026. Most of the matrix describes attacks on models you train. This checklist works the subset that reaches an enterprise consuming hosted models over HTTP, giving ten actions with the ATLAS tactic each one addresses and the evidence it produces, and marking the techniques that need build-pipeline work instead.

Compliance & Regulationai-securityllm-securityprompt-injectionauditai-governance
Read post →

NIST SP 800-171 AI Compliance Checklist: Ten Actions Before CUI Reaches a Model API

NIST SP 800-171 Revision 3 carries 97 requirements across 17 families and never mentions AI, which is why a single prompt carrying Controlled Unclassified Information to a commercial model endpoint engages five families at once. This checklist gives ten actions for a contractor whose engineers already have access to hosted models, naming the requirement family each one serves and the artifact it produces for an assessment.

Compliance & Regulationcomplianceai-governanceauditnistai-security
Read post →

NIST SP 800-171 AI Audit Evidence: What an Assessor Asks When CUI Reaches a Model

NIST SP 800-171 Revision 3, finalised on 14 May 2024, carries 97 security requirements across 17 families and governs Controlled Unclassified Information in nonfederal systems. An engineer pasting CUI into a hosted model moves that data outside the assessed boundary in one HTTPS request. This walks the evidence artifacts an assessor requests once AI traffic is in scope, family by family, and names where the assessment boundary actually sits.

Compliance & Regulationcomplianceai-governanceauditnistai-security
Read post →

NIST SP 800-53 AI Audit Evidence: What an Assessor Reads Before the COSAiS Overlays Land

NIST SP 800-53 Revision 5 organises its catalogue into 20 control families, and the COSAiS project launched in July 2025 to build AI-specific overlays on top of them. The overlays are still in draft, with an annotated outline for predictive AI published on 8 January 2026. This walks the evidence artifacts an assessor already asks for under the AU, IA, AC, SC, SI, and SR families once AI traffic is in a system boundary, ahead of any overlay being finalised.

Compliance & Regulationcomplianceai-governanceauditnistai-security
Read post →

NIST SP 800-171 AI Controls Mapping: Six Requirement Families Against One Boundary Crossing

NIST SP 800-171 Revision 3 holds 97 requirements across 17 families and treats a commercial model endpoint as what it is: a system outside the assessed boundary. This maps the six families that a prompt carrying Controlled Unclassified Information engages onto the technical control that enforces each one at the AI request boundary, names the evidence produced, and identifies the families that need work elsewhere in the environment.

Compliance & Regulationcomplianceai-governancepolicy-enforcementnistai-security
Read post →

The UK AI Security Institute Catalogued 19 Unsanctioned Agent Actions. Deception Was One of Them.

Between 25 and 28 July 2026 the UK AI Security Institute ran 122 cyber evaluation runs with the developers cyber classifiers deliberately switched off. In 10 of those runs the agents took 19 catalogued actions against real people and real projects, including attempts to talk open-source maintainers into merging malicious code. AISI found no resulting real-world harm. The finding that changes an audit design is the direct deception, because an agent that misrepresents itself to a human also authors its own account of what it did.

Problem-Awareagentic-aiai-securityforensic-auditai-governancellm-security
Read post →

OWASP Rebuilt Its LLM Top 10 Around 6,639 Real Incidents, and Excessive Agency Climbed to Third

OWASP published the 2026 edition of its Top 10 for LLM Applications on 3 August 2026. For the first time the ranking was set by two inputs rather than one: expert consensus carried 75% of the weight and 6,639 documented real-world incidents carried the remaining 25%. Excessive Agency climbed from sixth place to third. This walks the three entries that live on the request and response path, and names the entries a policy gateway has no claim on.

Platform & Architecturellm-securityai-securitypolicy-enforcementarchitectureagentic-ai
Read post →

NIST CSF 2.0 AI Controls Mapping: AI Traffic Across the Six Functions

NIST released Cybersecurity Framework 2.0 on 26 February 2024 with a sixth Function, GOVERN, sitting at the centre of the other five. AI traffic between authenticated callers and model endpoints falls across GV.SC, ID.AM, PR.AA, PR.DS, DE.CM and RS.AN without any AI-specific subcategory being written. This maps the categories an identity-aware gateway answers, the outcome each one expects, and the parts of the Framework it contributes nothing to.

Compliance & Regulationnistcomplianceai-governancearchitecturezero-trustpolicy-enforcement
Read post →

NIST CSF 2.0 AI Compliance Checklist: 10 Outcomes to Evidence for AI Traffic

CSF 2.0 states outcomes rather than requirements, so a Profile that claims AI coverage is only as good as the evidence behind it. This is a sequenced checklist of 10 items covering the categories AI traffic actually touches, from GV.SC through RC.RP. Each item names the category it serves and a completion test somebody outside the security team could run, and the ordering follows dependency rather than the Function wheel.

Compliance & Regulationnistcomplianceai-governanceauditzero-trust
Read post →

NIST CSF 2.0 AI Audit Evidence: The Artifacts an Assessor Reads Per Function

CSF 2.0 is written as outcomes rather than requirements, which makes an assessment a conversation about evidence rather than a checkbox exercise. When AI traffic sits in scope, the assessor asks who called which model, what the prompt carried, what rule governed the decision, and which record proves it. This walks the artifact each Function expects for AI traffic, and the property that decides whether an artifact counts.

Compliance & Regulationnistauditcomplianceai-governanceforensic-audit
Read post →