From the Cisco edition of November 5, 2026
Checkable AI: public-docs stack check finds Cisco AI Defense covers MCP runtime profiles and SOC export but not complete tamper-evident agent audit or public FedRAMP/IRAP/ISO 42001 attestation
Checkable AI · Independent AI controls knowledge base (docs-based product mapping) · Global product; Checkable regions include United States, EU, Australia
- Publisher
- Checkable AI
- Original publication
- Checkable AI knowledge base, last checked Oct. 19, 2026
- Source retrieved
- 2026-11-06
What happened
Why now: Nov. 5 Partner Summit and Nov. 4 Splunk posts position Cisco AI Defense as the active protection layer for agentic AI. Checkable AI’s Oct. 19, 2026 public-documentation stack check (40 findings; not a live-tenant test) finds supported capabilities such as MCP Security Profiles/runtime tool blocking and SOC telemetry export to Splunk/ServiceNow, while marking not covered: agent identity issuance, credential brokerage, approval gates for proposed actions, sandbox/emergency stop, and a complete tamper-evident per-agent record of tool calls and data access (logs only for policy-triggering traffic; rule-only API evaluations write no event). It also reports no public IRAP, ISO 27001 or ISO/IEC 42001 attestation for AI Defense and notes event-log storage in the US with limited points of presence.
Why it matters
Directly material for SLED buyers evaluating AI Defense against audit, residency and authorization requirements when partners pitch “trusted AI.” Does not itself document a government deployment; it constrains what can be claimed from vendor marketing alone.
Evidence and measured results
Independent docs-based control mapping last checked Oct. 19, 2026. Explicitly not a penetration test or live deployment assessment; some Cisco securitydocs pages were inaccessible to Checkable.
Limitations and uncertainty
Docs-only; dated Oct. 19 relative to Nov. 5 marketing; product may have changed; out-of-scope items are not automatically defects.
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-11-06; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- SLED buyers hear AI Defense closes the agent trust gap but need an evidence-based view of what the product actually documents.
- Stakeholders
- CISO
- AI platform owner
- Auditor/compliance
- Procurement
- Discovery questions
- Which agent audit and attestation requirements must you meet?
- Do you need FedRAMP or equivalent evidence for AI runtime controls?
- What compensating controls exist for agent identity and change approval?
- Value hypothesis
- Independent public-docs mapping can prevent overselling AI Defense as complete agent governance; it is not a lab test of a live tenant.
- Potential engagement
- Control-gap workshop aligning AI Defense documented scope to agency agent-governance requirements.
- Unsupported claims
- Live-tenant verification by Checkable
- That unsupported controls are defects rather than out-of-scope
- FedRAMP authorization status beyond what Checkable found public
Pre-sales engineering
Role takeaway
- Fit
- Useful scrutiny source when designing agent controls alongside Cisco AI Defense.
- Architecture and integration
- AI Defense for inventory, red teaming, runtime/MCP guardrails and SOC export; complementary systems needed for agent identity, approval gates and tamper-evident action ledgers.
- Prerequisites
- Inventory of MCP servers and agents
- SIEM/ServiceNow integration plan
- Written audit requirements
- Constraints
- Docs-based check, not penetration test
- Last checked 19 Oct 2026
- Some Cisco securitydocs pages inaccessible to Checkable
- Security
- Do not treat policy-trigger logs as a complete agent action history; design export and integrity separately if required.
- Proof of value
- Reproduce key Checkable findings against current release notes
- Confirm which MCP profiles are attached in staging
- Identify compensating control for administrative audit gap
Delivery
Role takeaway
- Work
- AI Defense scope-and-gap matrix for agent production readiness.
- Dependencies
- Current AI Defense release notes
- Agency audit policy
- Identity/PAM owners
- Ownership
- Security architecture lead with AI platform and compliance
- Skills and adoption
- Teams must distinguish traffic guardrails from agent lifecycle governance.
- Governance checkpoints
- Attestation evidence review
- Audit-log completeness decision
- Compensating-control sign-off
- Acceptance criteria
- Proposed: every required control mapped to AI Defense or a named compensating system
- Proposed: no production expansion where audit gaps are unmarked
- Risks
- Stale findings after product updates
- Docs-only blind spots
- False assurance from partial SOC export
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
AI Defense is strongest as inventory, red teaming, runtime/MCP traffic mediation and SOC export; agent lifecycle identity, approval and write-once audit need complementary systems.
Governance
Who approves, reviews and stays accountable for outcomes?
Buyers should map required controls to AI Defense or named compensating controls before treating AI Defense as complete agent governance.
Security and privacy
What data, permissions and controls need testing?
Policy-trigger logs are not a full agent action history; residency of AI Defense events and attestation gaps matter for regulated SLED workloads.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
No workforce findings; control completeness affects auditor and operator workload more than end-user accessibility.
Procurement
What should contracts, pricing and exit terms secure?
Require current release notes, Trust Portal evidence under NDA if needed, and contractual clarity on audit-log completeness and residency.
Operating model
Which teams own the service once it runs?
Separate traffic guardrail operations from agent identity, change approval and evidence retention owned by identity/PAM and compliance teams.
Publication history
- 2026-11-05Cisco · Issue 084 resources
Stable resource ID: checkable-ai-cisco-ai-defense-control-gaps-audit-attestation-20261019