Asset Management

Know what you have.Know what’s risky.

Continuous discovery of every model, MCP, knowledge base, tool, and permission across your AI stack. Each tagged with concrete risks and severity, kept fresh as you ship.

Book your demoResearch
general-analysisAsset Management
Systems
12
Agents and tools
94
Injection points
17
Breached risk tags
72 critical
Architecturesupport-agent
user_messagesupport-agentread_ticketsearch_kblookup_orderbilling-agentrefunds.createissue_creditInjection pointticket_body
Top vulnerabilities6 simulations

  1. Indirect prompt injection

    LLM019 of 40 attempts

    Critical

  2. Excessive agency

    LLM066 of 32 attempts

    High

  3. System prompt disclosure

    LLM075 of 48 attempts

    High

  4. PII disclosure

    LLM024 of 36 attempts

    Medium

  5. Billing misinformation

    LLM092 of 30 attempts

    Low

Continuous discovery

Every model, MCP, knowledge base, tool, and permission across your stack—catalogued automatically and kept fresh.

Risk-aware tagging

OWASP LLM Top 10 categories applied to every asset with concrete evidence, so you can see what matters first.

No-touch integration

Connects to your cloud, code, docs, and agent infra in minutes. No agents installed, no rewrites required.

Built for visibility

See your AI stack
clearly.

  • Connects to your stack in minutes
    Cloud, code, docs, and agent infrastructure — no agents, no rewrites.
  • Discovers every AI asset
    Models, MCPs, knowledge bases, tools, and permissions in one inventory.
  • Tags risks automatically
    Each asset labeled against OWASP LLM Top 10 with concrete evidence.
  • Stays current as you ship
    Re-scans on every change so the inventory never drifts.
inventory.yaml
# Connect your stack and we keep the inventory fresh:
# $ ga inventory sync

integrations:
  - aws
  - github
  - gcp
  - notion
  - slack
discover:
  - models
  - mcps
  - knowledge_bases
  - tools
  - permissions
schedule: daily
tag_with: owasp_llm_top10

Inventory depth

Know every AI asset.

Asset Management gives security teams the map they need before testing or enforcement begins. It continuously discovers what exists, how it connects, who owns it, and where risk is accumulating.

Model and endpoint inventory

Catalog hosted models, provider accounts, app endpoints, embedded assistants, and shadow AI usage across cloud and code repositories.

Knowledge-base exposure

Find sensitive documents, poisoned retrieval content, stale indexes, risky citations, and data sources attached to the wrong assistant.

MCP and tool graph mapping

Map MCP servers, plugins, tools, scopes, service accounts, and permission chains that can create excessive agency or exfiltration paths.

Risk ownership and drift

Assign assets to teams, track changes over time, and flag newly risky configurations before they become production incidents.

How discovery works

Connect

Read from existing systems

Integrate with cloud accounts, repositories, observability tools, document stores, identity providers, and agent platforms.

Graph

Build the AI asset map

Link models, prompts, tools, identities, data sources, and deployment surfaces into a single graph security teams can query.

Score

Attach evidence-backed risk

Evaluate each asset against OWASP LLM risks, data sensitivity, tool privileges, external exposure, and policy coverage.

Route

Send fixes to the right owners

Create prioritized remediation paths for engineering, security, compliance, and platform teams with the asset context attached.