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Numbat
Numbat is a command-line tool from Perplexity AI for seeing what supported AI agents did on a computer. It can read saved session artifacts, receive live activity through hooks and plugins, apply local detection rules, and produce records for investigation.
The initial v0.1.1 public release includes binaries for macOS, Linux, and Windows. Monitoring is the default. Blocking is opt-in, works only through supported synchronous pre-action hooks, and depends on the agent host carrying out Numbat's deny response. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.
What it is
An endpoint view of agent activity
Numbat normalizes activity from supported saved sessions, live hooks and plugins, and OTLP or HTTP logs into one event model. The same CEL rule engine can evaluate live and at-rest events locally.
Why it stands out
Live monitoring and after-the-fact reconstruction
One tool can inventory supported agents, scan retained session artifacts, build per-session timelines, and monitor supported live actions. That helps a team connect what an agent proposed or recorded with the source event behind a finding.
Availability
Public code and cross-platform release
The public repository includes documentation, rules, schemas, and release downloads for macOS, Linux, and Windows on amd64 and arm64. It can also be installed with a current Go toolchain or built from source.
Why it matters
What makes it useful
Agent activity is often split across session files, hook callbacks, logs, and different host formats. Numbat gives developers and operators one local event and rule model for reviewing that activity during a run or reconstructing it later, without requiring every supported agent to produce the same native record shape.
What to know
Where it fits
Numbat belongs beside coding-agent and endpoint operations rather than inside the model itself. It can help with inventory, monitoring, investigation, and narrowly supported pre-action blocking; it is not a complete endpoint security boundary or proof that a finding represents a compromise.
Notable points
What stands out
The coverage matrix is the practical source of truth: support differs by agent, operating system, saved-artifact format, live-capture mechanism, and enforcement hook. Some integrations have both local artifact and hook coverage, while others are live-only, deferred, preview-bound, or monitor-only.
Before using
What to review
Check the current coverage row for every agent and host you expect to monitor; a supported product name does not mean every desktop, CLI, IDE, cloud, or gateway mode is covered.
Start in monitor mode and verify that the intended hook runs and records arrive. The project says hook status checks configuration on disk, not whether the host trusted, loaded, or executed it.
Treat outputs and state as sensitive endpoint data. Records can retain redacted commands, paths, URLs, content previews, endpoint identity, model context, and stable project-path hashes.
Do not treat redaction as a data-loss-prevention boundary. Review records and case evidence before sharing them, and protect local output, sequence state, hook configuration, and any configured HTTP sink.
Test enforcement against the exact host and failure behavior you rely on. Malformed input, relevant evaluation errors, oversized payloads, or output failures can suppress Numbat's deny response.
Recheck release maturity and compatibility before wider rollout. The security policy says only the most recent minor release receives security fixes.
Reader fit
Who may find it relevant
Developers and teams running supported coding, desktop, IDE, or gateway agents on their own endpoints.
Operators who need a local first pass over agent session artifacts, live activity, findings, and timelines.
Teams comparing monitor-only visibility with narrowly supported pre-action blocking.
Less relevant for readers who want a consumer chatbot, a hosted dashboard with no local setup, or a universal security control for every agent surface.
Editorial note
Why LifeHubber lists it
Numbat brings live agent monitoring and saved-session reconstruction into one local tool. That gives teams a concrete way to compare what different agent hosts expose, what can be detected after the fact, and where a supported pre-action hook can intervene before a tool runs.
Source links
Source materials
Reader note
Before relying on this entry
LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.
What to explore next
Compare monitoring with policy controls and trace review.
Numbat watches supported agent activity and can ask certain hosts to deny a matched pre-action event. These pages continue the question from two other directions: a broader runtime policy layer and a simpler view of one coding agent's saved trace.
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