ConsultingWorkbench-backed AI security engagements — map, attack, defend, and prove your AI systems.
Scope a Review
← AttestationsIssuedATT-AISC-2025-0534

aisecurity.llc

AI SECURITY · PRIVACY · TRUST

SECURITY REVIEW ATTESTATION

Independent Assessment · Evidence-Based · Public-Safe

A

ACME Corp

acmecorp.io

ACME Corp engaged aisecurity.llc to conduct a security review of the systems, processes, and public trust surfaces described below.

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Governance Evidence Sprint

Structured evidence collection and control mapping against NIST AI RMF and ISO 42001 frameworks.

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AI Policy Framework Review

AI use policy, model governance charter, acceptable use, and incident classification policy review.

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NIST AI RMF Alignment

Control mapping and gap analysis against the four NIST AI RMF core functions: Govern, Map, Measure, Manage.

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Buyer Evidence Pack Review

Assessment of governance artifacts suitable for enterprise procurement, board reporting, and regulatory inquiries.

Systems / Features in ScopeACME Corp AI governance program covering the AcmeAssist product line: AI use policy, model governance charter, risk register, incident classification procedure, NIST AI RMF self-assessment, and related evidence artifacts.
Review TypePolicy review, control evidence assessment, NIST AI RMF gap analysis, and governance maturity evaluation against ISO 42001 / AIMS readiness criteria.
Engagement IDAISC-2025-0534
Engagement PeriodJune 9, 2025June 27, 2025
Report DeliveredJuly 1, 2025
74/ 100

Developing

ACME Corp's AI governance program is actively developing with a clear foundation in place. Core policies exist and the risk register is maintained. Two high-priority gaps were identified: the Model Governance Charter lacks an approved ownership and accountability chain, and NIST AI RMF Measure function evidence is incomplete. A targeted 90-day remediation roadmap was delivered.

2High findings
8Medium findings
15Low findings
6Informational

AI Governance

Policies, accountability structure, model lifecycle, and oversight mechanisms.

NIST AI RMF — Govern

Governance structures, policies, roles, and accountability for AI risk.

NIST AI RMF — Map

AI use case classification, risk categorization, and stakeholder impact mapping.

NIST AI RMF — Measure

Metrics, evaluation, and ongoing risk measurement practices.

NIST AI RMF — Manage

Risk response plans, incident procedures, and ongoing risk management.

Privacy & Data Governance

Data provenance, consent, and model training data governance.

Third-Party AI Governance

Vendor AI usage policies, sub-processor governance, and LLM provider oversight.

AI Incident Management

Classification procedure, escalation paths, and AI-specific incident scenarios.

External Governance Evidence

Buyer-facing governance artifacts, disclosures, and evidence package readiness.

Model Continuity & Resilience

Fallback procedures, model version control, and degraded-mode governance.