Cranium
Overview
Product details compiled from public sources, each with a citation.
- Vendor
- Cranium AI1
- Description
- Platform that discovers and inventories enterprise AI systems, generates AI bills of materials, red teams models, and maps risks to regulations such as the EU AI Act and NIST AI RMF.2
- Deployment
- SaaS3
- Status
- Active1
- Compliance
- SOC 2 Type 25 (company-level, see Methodology)
Matrix Coverage
Where this product defends, by asset class and NIST CSF function. The Coverage column shows whether each asset is Primary, Secondary, or Adjacent to what the product does. The table omits empty rows and columns.
| Asset class | Govern | Identify | Detect | Coverage | Source |
|---|---|---|---|---|---|
| AI-Workload Platforms | Govern: Not covered | Secondary | 4 | ||
| AI Model | Primary | 2 | |||
| AI Agent Identities | Govern: Not covered | Detect: Not covered | Secondary | 4 |
Framework Relevance
These frameworks include controls relevant to the asset classes Cranium defends. This is an editorial inference from the AI Defense Matrix asset-level crossmap, not a statement that Cranium AI implements these controls or is certified against them.
Expand Collapse
| Framework | Asset class | Relevant controls |
|---|---|---|
| NIST IR 8596 | AI-Workload Platforms | Containers, microservices, and libraries (AI-specific subset); inference endpoints (platform side) |
| AI Model | Models; Algorithms (model configuration) | |
| AI Agent Identities | Agents as autonomous principals; Keys; Integrations and permissions | |
| CSA AI Controls Matrix | AI-Workload Platforms | Infrastructure Security; Threat & Vulnerability Management |
| AI Model | Model Security; Governance, Risk and Compliance | |
| AI Agent Identities | IAM; Governance, Risk and Compliance | |
| ISO 42001 | AI-Workload Platforms | A.6 AI system life cycle; A.4 Resources for AI systems |
| AI Model | A.6 AI system life cycle; A.10 Third-party and customer relationships; A.5 Assessing impacts of AI systems | |
| AI Agent Identities | A.9 Use of AI systems; A.3 Internal organization; A.5 Assessing impacts of AI systems | |
| Google SAIF | AI-Workload Platforms | Expand strong security foundations; secure and harden the AI deployment environment |
| AI Model | Protect the AI model; ensure model integrity, provenance, and weight security | |
| AI Agent Identities | Focus on Agents (explicit SAIF section); identity, authorization, and delegation controls | |
| SANS Critical AI Security Guidelines | AI-Workload Platforms | Conventional Security Controls (host AI within the existing ISMS; authentication and access controls; encryption at rest); AI Supply Chain Management (local vs. SaaS hosting trade-offs; internal model garden) |
| AI Model | Conventional Security Controls (protect model parameters with least privilege, encryption at rest, runtime obfuscation, and trusted execution environments); Data/Model Engineering Controls (adversarial training; alignment and fine-tuning); AI Supply Chain Management (public-model caution; transfer-attack exposure) | |
| AI Agent Identities | Secure Agentic Systems and AI Autonomy Controls (defined function scope; API and function-call gating; escalation and fallback); Limit Model Behavior (least-privilege focused functionality; human oversight; override capabilities) | |
| MITRE ATLAS | AI-Workload Platforms | AML.T0010 AI Supply Chain Compromise; AML.T0012 Valid Accounts (platform credential abuse); container and inference-server exploits |
| AI Model | AML.T0043 Craft Adversarial Data; AML.T0024 Exfiltration via AI Inference API (subtechniques: AML.T0024.001 Invert AI Model and AML.T0024.002 Extract AI Model); AML.T0018 Manipulate AI Model (integrity and backdoor) | |
| AI Agent Identities | AML.T0053 AI Agent Tool Invocation; credential and delegation-chain abuse | |
| OWASP AI Exchange | AI-Workload Platforms | Development-time threats: supply chain attacks, model-platform CVEs, container escape |
| AI Model | Development-time and runtime model threats: model inversion, extraction, evasion, poisoning | |
| AI Agent Identities | Runtime threats: unauthorized agent actions, capability abuse, delegation chain exploitation | |
| OWASP LLM Top 10 | AI-Workload Platforms | LLM03 Supply Chain (compromised AI platform components); LLM04 Data and Model Poisoning (via platform) |
| AI Model | LLM03 Supply Chain; LLM04 Data and Model Poisoning; LLM09 Misinformation | |
| AI Agent Identities | LLM06 Excessive Agency; LLM05 Improper Output Handling; unauthorized actions by AI agents | |
| OWASP Agentic Security Top 10 | AI-Workload Platforms | ASI04 Agentic Supply Chain Vulnerabilities (model and tool-platform components); ASI08 Cascading Failures (platform fault propagation) |
| AI Model | ASI04 Agentic Supply Chain Vulnerabilities (model provenance, weights, and dynamic loading) | |
| AI Agent Identities | ASI03 Identity and Privilege Abuse; ASI10 Rogue Agents; ASI09 Human-Agent Trust Exploitation; ASI02 Tool Misuse and Exploitation (when tied to agent permissions) |
Provenance
Last sourced 2026-07-17.
Expand Collapse
Sources
- Cranium homepage
- Cranium platform overview
- “scan your codebases, internal environments, cloud configurations and agentic layer to surface undocumented or unapproved AI systems”
- Cranium Arena
- Cranium Discover page
- “monitors cloud changes, alerts and access controls”
- “maps agents, the tools they invoke, and the agents they reach”
- Cranium SOC 2 Type 2
- “Cranium has a positive SOC 2 Type 2 attestation report”
Changelog
-
Refreshed coverage source citations and quotes against the current vendor platform pages.
-
Refined matrix coverage against the current platform pages.
-
Added to the catalog from the Cranium documentation.
Found an error? Corrections are welcome. Suggest an edit.