{"resourceId":"checkableai-openshift-ai-security-controls-assessment-20261104","versions":[{"version":"external-c3cfa68439146021360dbae21605ff28444879ececf860cac0c49bdd5d139164","resource":{"id":"checkableai-openshift-ai-security-controls-assessment-20261104","title":"Checkable AI: Red Hat OpenShift AI security controls assessment (42 findings, last checked 4 Nov 2026)","organization":"Checkable AI","sector":"Independent AI controls research","geography":"Global product assessment (US/EU/AU frameworks referenced)","publishedAt":"2026-11-04","publicationDate":"2026-11-04","eventDate":"2026-11-04","sourceName":"Checkable AI","sourceLabel":"Independent documentation-based AI Stack Check of OpenShift AI 3.5 / Inference / OGX / MCP gateway controls","sourceUrl":"https://checkableai.com/stack-check/platforms/red-hat-openshift-ai/","evidenceClass":"independent-research","outcomeClass":"mixed","topics":["governance-procurement","data-security","developers-agents","operating-model"],"finding":"Checkable AI’s OpenShift AI stack check (last checked 4 November 2026) reports 42 documentation-based control findings across identity, authorisation, runtime, mediation, observability, agentic MLSecOps and governance. Multiple high-interest gaps are marked Not addressed, including agent identity tied to an owner/release record, tamper-proof administrative audit beyond kube-apiserver config changes, runtime assurance/attestation of inference containers, and SBOM/provenance for MCP servers. The research notes AgentRuntime/OpenShell and MCP gateway capabilities as Developer/Technology Preview and states findings reflect public vendor docs, not a live penetration test. Newly relevant alongside the Nov. 5 OpenShift AI pipeline CVE batch because it frames control debt around the same expanding agent/MCP surface.","sledRelevance":"Gives SLED architects an independent checklist when justifying OpenShift AI for regulated workloads: which controls are documented GA versus Preview/not addressed. Does not replace agency ATO testing.","evidence":"Page states 42 findings, last checked 4 November 2026; area tallies; detailed Not addressed notes on Administrative Audit (no tamper-proof record; MLflow/OGX logs not tamper-proof), Runtime Assurance, Agent ID, MCP SBOM/provenance; scope covers OpenShift AI 3.5, Red Hat AI Inference, OGX, Connectivity Link MCP gateway.","architectureImplications":"Plan compensating controls outside the product for audit immutability, runtime attestation and MCP supply-chain provenance if those are ATO requirements.","governanceImplications":"Treat Preview agent/MCP features as non-production for high-assurance SLED until support and control evidence mature; map each required control to vendor doc status.","securityPrivacyImplications":"Highlights missing tamper-evident AI audit and runtime assurance—material for continuous monitoring plans even when cluster audit exists.","caveats":"Documentation review, not a live deployment test. Last checked 4 Nov—one day before this edition’s pipeline CVE wave, so those CVEs are not integrated into the check. Independent site; verify against current Red Hat release notes before contractual use.","streamIds":["red-hat"],"roles":{"sales":"Sales framing: independent control-coverage narrative for cautious SLED buyers. Lead with what is documented versus Not addressed (audit immutability, runtime assurance, agent identity, MCP provenance). Offer a controls-gap workshop—not a claim that OpenShift AI fails every control. Unsupported: presenting Checkable scores as a formal certification or live exploit proof. Label recommendations as interpretation with limited applicability to the inspected evidence.","engineering":"Engineering framing: crosswalk Checkable Not addressed items to the customer’s ATO catalog; design compensating SIEM/WORM audit, image signing, and MCP allow-lists. Proof of value is a completed gap matrix with owners, not a red-team report derived solely from this documentation review. Label recommendations as interpretation with limited applicability to the inspected evidence. Confirm transferability to the local SLED estate before committing budget.","delivery":"Delivery framing: produce a control matrix mapping each Checkable finding to Red Hat doc status, compensating control and owner. Gate Preview MCP/agent features behind CAB. Risk: freezing all AI work based on documentation gaps that the agency’s authorization boundary does not actually require. Label recommendations as interpretation with limited applicability to the inspected evidence. Confirm transferability to the local SLED estate before committing budget."},"roleDetails":{"sales":{"customerProblem":"Buyers lack an independent view of which OpenShift AI AI-security controls are documented GA versus missing or Preview.","stakeholders":["CISO","ATO/authorizing official","AI platform owner"],"discoveryQuestions":["Which controls are must-have for your ATO?","Are agent/MCP features in scope this year?","Do you require tamper-evident AI audit?"],"valueHypothesis":"A controls-gap workshop can focus spend on compensating controls that matter for the agency’s authorization boundary.","potentialEngagement":"Two-week OpenShift AI control crosswalk using Checkable findings and Red Hat release notes.","unsupportedClaims":["Checkable is a certification","Live exploitability of every Not addressed item","OpenShift AI is unsuitable for all SLED"]},"engineering":{"fit":"OpenShift AI 3.x estates evaluating agent/MCP/OGX controls for regulated use.","architectureIntegration":"Add external immutable logging, signing/attestation, MCP gateway policies alongside product features.","prerequisites":["Current release notes","ATO control catalog","network policy capability"],"constraints":["Docs-only evidence","Preview features unsupported in some disconnected modes"],"security":"Gaps concentrate in audit integrity, runtime assurance and MCP supply chain.","proofOfValue":["Completed gap matrix","Compensating control designs accepted by security"]},"delivery":{"work":"Control matrix, compensating designs, Preview feature gates.","dependencies":["Security architecture approval","logging platform"],"ownership":"Security architecture with platform engineering","skillsAdoption":"Teams learn to operate Preview vs GA feature policy.","governanceCheckpoints":["ATO evidence review","Preview enablement CAB"],"acceptanceCriteria":["Signed gap matrix","Documented bans/allow for Preview MCP/agents"],"risks":["Over-blocking low-risk labs","Stale Checkable snapshot vs new CVEs"]}},"retrievedAt":"2026-11-06T22:11:51-06:00","enrichedAt":"2026-11-06T22:11:51-06:00","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Not a primary focus; Preview agent tooling implies limited supported paths for broader workforce use.","procurementImplications":"Use as a question bank in RFP/ATO evidence requests—ask vendors to show GA controls for audit immutability, runtime assurance and MCP provenance.","operatingModelImplications":"Security and platform teams must own compensating controls where Checkable marks Not addressed.","sourceVerification":{"openedUrl":"https://checkableai.com/stack-check/platforms/red-hat-openshift-ai/","referenceExcerpt":"No tamper-proof record; kube-apiserver audit covers config changes, MLflow traces and OGX logs are not tamper-proof.","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}