Discovering Every Shadow AI Agent Agency-Wide

Program offices and contractors stand up chatbots, agents, and MCP tools outside CIO review, so agency AI use case inventories miss projects that federal guidance expects them to report. PointGuard AI discovers AI assets across clouds, repositories, and runtime telemetry and builds one deduplicated registry with owners and data access, giving CIOs a complete starting point.

Agency AI inventories depend on self-reporting that misses projects.

• Contractors deploy AI tools inside program environments.
• Staff adopt public AI tools and browser extensions.
• MCP servers connect agents to agency systems without review.
• Inventory reporting is manual and quickly outdated.

AI Discovery & Inventory and Shadow AI Control build a continuous registry and enforce acceptable use.

1. Discover across vectors. Scan cloud accounts, repositories, network traffic, runtime telemetry, and endpoints for models, agents, and MCP servers.

2. Build one registry. Deduplicate findings and record owner, program, contractor, purpose, and data access for each asset.

3. Classify and decide. Flag systems that touch sensitive data or affect rights or safety, and route them for review, approval, or restriction.

4. Keep it current. Rescan continuously and export the inventory to support agency reporting.

• OWASP Top 10 for LLMs: LLM02 Sensitive Information Disclosure and LLM03 Supply Chain, covering data exposure through unreviewed tools and unvetted third-party components.
• OWASP Top 10 for Agentic Applications: ASI04 Agentic Supply Chain Vulnerabilities and ASI10 Rogue Agents, addressing unvetted agent components and agents operating outside governance.
• NIST AI RMF: GOVERN sets acceptable use; MAP inventories AI systems; MEASURE assesses exposure; MANAGE restricts unapproved tools.