Book a walkthrough
ColossalX
Sign inBook a walkthrough

SeeAI inventory and agent mapx, found

AI inventory and agent map, with how each was found.

A governed registry and a live map of agents found in code, traffic, CI and the cloud.

How it works

Specs

AI inventory and agent map, in detail

Delivery and data

Delivery
SaaS, from one login.
Isolation
Each customer runs in an isolated workspace with its own database.
Certifications
None held. Frameworks are mapped to and assessed against.

Frameworks

OWASP Top 10 for Agentic Applications
Assessed per agent against: Each registered agent, against ASI01 to ASI10.
EU AI Act
Mapped to: An owned agent inventory, cross-mapped.
ISO/IEC 42001
Mapped to: The same inventory control, with evidence.
NIST AI RMF
Mapped to: Inventory under Map and Govern.
See the frameworks

Last reviewed 6 Oct 2026

Found, then ownedIllustrative

Found, then owned: refunds-agent found calling registry; pricing-agent found calling registry; repo-agent to registry; registry to owner (owner named); registry to provider A; registry held for a person before customers (awaiting approval).

In shortShadow agentsShadow agents are AI agents running without being registered, owned or approved: a script calling a model with a team key, a low-code agent built in an afternoon, or a vendor agent working on internal data. Unlike shadow AI tools, they act on their own, calling models and tools with nobody accountable for what they do. In the glossary

AI-SPM for agents, in ColossalX: a governed registry and a live AI Agent Map. Each agent is labelled with how it was found, mapped to the models, tools and data it reaches, recognised by its behaviour, and kept out of production until an accountable owner and a second approver have admitted it.

An agent nobody registered starts calling models, and nobody is accountable for it.

ColossalX finds it in traffic, code or CI, maps what it reaches, and asks for an owner.

How it works

From an agent nobody registered to an owned one.

One agent found in a repository: its threat brief, its place on the map, and the two people who admit it.

Workflow · an agent found in code, ownedIllustrative

01 Found in code

A repository scan finds an agent and the AI libraries it imports.

02 A threat brief

Its own code gives a brief: abilities, risks and upgrades.

03 On the map

It joins the map with its calls, declared tools and data.

04 Owned, then admitted

An owner, then a second approver, before it reaches production.

What you see

The AI Agent Map, with what each agent reaches.

Agents, model providers and models on one graph, built from what each agent declares and what the gateway sees.

  1. Agents enter four ways
  2. Recognised by behaviour
  3. Mapped with blast radius
  4. Owned before admitted
Read the detail, step by step4
  1. Agents enter four ways. Registered by hand, found in code or traffic, or attested from CI. Each agent carries a label saying how it entered: registered by hand, found in code, discovered in gateway traffic, or attested from CI and the cloud.
  2. Recognised by behaviour. Fingerprinting recognises an agent by what it does, not its key. Behavioural fingerprinting shows when an agent's behaviour moves from its baseline, and finds which known agent an anonymous caller really is.
  3. Mapped with blast radius. The map shows what each agent calls, declares and delegates to. Click an agent to light up everything it can reach. The attack-path view shows routes from untrusted entry points to sensitive data.
  4. Owned before admitted. An owner, a second approver and a guardrail profile before production. Registered is not approved. Workspaces roll admission out monitor-then-enforce, with time-boxed exceptions.
Agent registryIllustrative

An illustrative agent registry: each agent with how it was found (registered by hand, found in code, attested from CI or seen in gateway traffic), its owner and its status. An unknown caller seen in traffic is named and waits for an owner, because registered is not approved.

3notes
  1. How each agent was found
  2. Seen in traffic, waiting for an owner
  3. Registered is not approved

How it connectsx, found

Where a found agent goes next.

Finding an agent is the start. The same record carries it through admission, policy, testing and the twin.

  1. Admission

    An owner, a second approver and a guardrail profile; credentials carry what was measured.

  2. Guardrails

    Its requests and tool calls are checked at the gateway under its own credential.

  3. Red-teaming

    A registered agent can be attacked in-path, with authorisation, through your real controls.

  4. CyberTwins

    Governed agents can be projected into a twin and attacked there, not in production.

Honest by design

What it does, and what it does not.

Agent record · labelled, not guessedIllustrative

Agent record · labelled, not guessed: Agent pricing-agent; How found Discovered in traffic; Risk score Provisional; Owner Not yet named; Admission Monitor, until approved. Provenance kept.

What it does not do

x, not measured

Tools and data on the map are what each agent declares; model links come from traffic.

All 4 limits
  • The identity gate ships in monitor. Refusing unenrolled agents at the gateway is your decision.
  • Attack paths need your data assets catalogued; without them the map shows none rather than guessing.
  • Cloud placement is proven on AWS; other cloud connectors are built but not yet proven.

How we know

  • Model, provider and delegation links on the map are observed from gateway traffic.
  • A credential used with the wrong behaviour raises an incident.
  • A risk score that comes from discovery is marked provisional.
  • Each agent keeps an append-only history of who acted on it, and why.

Questions

Questions buyers ask

What is AI security posture management (AI-SPM)?

AI security posture management, or AI-SPM, is the practice of knowing which AI systems an organisation runs, how they are configured and what they can reach, and keeping that picture current. For agents, it starts with a registry, a map of what each agent touches and a record of how each one was found.

What is an AI agent registry?

An AI agent registry is the governed catalogue of the agents a company runs. In ColossalX each entry records how the agent was found, who owns it, its trust zone, its guardrail profile and whether it is admitted to production, with an append-only history of what was done to it and why.

How does ColossalX find agents nobody registered?

ColossalX finds agents calling through its gateway without a registration, agents in scanned repositories, and agents attested from CI or the cloud. Behavioural fingerprinting matches an anonymous caller to a known agent where it can; one it cannot match is shown as new and needs an owner.

What is behavioural fingerprinting for AI agents?

Behavioural fingerprinting recognises an agent by what it does rather than by the key it presents: the models it calls, the tools it uses and the shape and rhythm of its requests. ColossalX keeps a fingerprint per agent, shows when behaviour moves from its baseline, and spots a credential used by the wrong agent.

What is the blast radius of an AI agent?

The blast radius of an AI agent is everything it could affect if it were compromised: the models it calls, the tools and data it declares and the agents it delegates to. On the AI Agent Map, clicking an agent highlights all of it, and an attack-path view shows routes to sensitive data.

Related

Where to look next.

Next step

Know your x.

See AI inventory and agent map on your own questions: what you run, what it does, and whether your defences hold.

Book a walkthrough Email us instead
  1. 01Tell us what you run
  2. 02See the four verbs on it
  3. 03Decide where to start