13 of 13 requirements
Export view:AI Security Posture Management
SPM · 11- SPM-001Live test
Classify previously unseen AI applications on first encounter
Identify and risk-score an AI application the platform has not seen before, without waiting for a signature, category list or catalog update, and show the evidence behind the classification.
- Why it matters
- Waiting for a catalog update leaves every new tool ungoverned during the period it is most likely to be tried.
- How to verify
- An AI tool the vendor has not seen before is classified and risk-scored on first use, with the evidence shown.
Area: AI Security Posture Management
- SPM-002Live test
Detect AI use at the browser point of use
Show visibility in Chrome, Edge, Safari and Firefox where supported, including prompt context and account plan.
- Why it matters
- The browser is where most employee AI use happens, so it is the first place visibility has to work.
- How to verify
- Pilot users' AI use in each supported browser appears with prompt context and account plan.
Area: AI Security Posture Management
- SPM-003Live test
Detect endpoint AI activity beyond the browser
Identify desktop clients, IDEs, coding assistants, CLI tools and local agents on managed Windows and macOS endpoints.
- Why it matters
- Desktop apps, IDEs and CLI tools carry a growing share of AI use, and browser-only controls never see them.
- How to verify
- Desktop assistants, coding tools and CLI tools used by pilot users appear, attributed to user, device and application.
Area: AI Security Posture Management
- SPM-004Live test
Detect direct model-provider API calls from employee devices
Attribute provider, process, device, user and destination for direct API use with no browser involved.
- Why it matters
- Scripts and tools that call model APIs directly bypass every browser control and often carry the most sensitive information.
- How to verify
- A direct API call from a pilot device is attributed to provider, process, user and destination.
Area: AI Security Posture Management
- SPM-005Live test
Discover local model runtimes and offline AI installations
Identify installation and running process for tools such as Ollama or LM Studio.
- Why it matters
- Local models move data off the monitored path entirely.
- How to verify
- A local runtime installed on a pilot device is discovered and cataloged.
Area: AI Security Posture Management
- SPM-006Live test
Discover AI embedded in sanctioned SaaS
Identify AI features inside existing SaaS tools, such as Google AI Mode.
- Why it matters
- AI features switched on inside approved SaaS create new data flows without a new application to approve.
- How to verify
- A common SaaS application is identified and cataloged as an AI tool due to its embedded AI features.
Area: AI Security Posture Management
- SPM-007Walkthrough + Documentation
Provide visibility for unmanaged endpoints
Use approved SaaS/API methods where no endpoint agent can be installed.
- Why it matters
- Contractors and personal devices still reach corporate AI tenants, and some will never run an agent.
- How to verify
- The vendor shows and documents the coverage method for an unmanaged device in your environment.
Area: AI Security Posture Management
Distinguish personal, free and guest accounts from sanctioned enterprise tenants
Report a reliable account-type split at the point of use and allow policy to vary depending on account plan.
- Why it matters
- Contractual protections attach to the enterprise tenant, not the domain. A personal account reaches the same URL with none of them.
- How to verify
- Enterprise, personal and unauthenticated use of the same tool are each identified and handled per policy.
Area: AI Security Posture Management
- SPM-009Walkthrough
Risk-score AI tools, connectors and agent workflows
Configurable factors such as vendor location, training on inputs, trust-center availability, account tier, autonomy, data sensitivity and tool power.
- Why it matters
- The risk in an AI tool usually sits in its data-handling terms, which change without the domain changing.
- How to verify
- Risk scores, with sources and factors, for five tools.
Area: AI Security Posture Management
- SPM-010Live test
Define default treatment for newly discovered AI services
Apply a documented default rule until the service is assessed as sanctioned, restricted or prohibited.
- Why it matters
- New tools arrive faster than they can be assessed, so the default decides what happens in the meantime.
- How to verify
- A tool first used during the pilot receives the documented default treatment.
Area: AI Security Posture Management
Support the AI tool approval and review lifecycle
Define and track unapproved versus approved AI tools and MCP servers.
- Why it matters
- Without a governed approval path, teams route around the control.
- How to verify
- Walk a tool or MCP server request from intake to a recorded decision.
Area: AI Security Posture Management
Agent & MCP Governance
AGT · 2Discover the MCP servers and connectors employees attach to their AI clients
Inventory local and remote MCP servers reached from desktop, IDE and CLI AI tools with owner, scope and exposure.
- Why it matters
- MCP-capable clients now ship inside IDEs, terminals and desktop apps, and each connector is a new path to corporate data.
- How to verify
- Local and remote MCP servers used by pilot users appear with client, owner, scope and exposure.
Area: Agent & MCP Governance
Map the actions available via each connector.
Show, per connector/MCP server, what actions are available and which are currently enabled.
- Why it matters
- Approving a connector without knowing which actions it exposes and which are enabled leaves the scope of available functionality unclear.
- How to verify
- For three connectors you name, the console lists the actions each exposes and shows which are currently enabled.
Area: Agent & MCP Governance