Don’t get hacked like

Explore the threats

Normal network activity.

This visual is a synthetic design study, not live product telemetry. Familiar relationships remain stable while recurring activity varies. The dot-matrix Earth fades into the baseline of directed workload connections, with no flagged anomalies. Discovery reveals seven illustrative connections across three related groups. The camera zooms in as shared workload relationships gather into three cases: a new feature, a scheduled job, and unusual worker activity. AI agents investigate the cases in parallel using deployment, code, schedule, process, and access evidence. Two cases receive explanations and dim in place. The third expands into its observed network context and supporting findings for human review. The proposed next check is to verify the entry point and scope the access. The example resolutions are scripted for this study. Context relationships are independent observations, not a complete agent execution. The fine grid and tracking marks are visual guides, not measured telemetry. The graph represents existing directed workload connections. Light, Dark, and Green are color treatments of the same graph and motion. Colors can be customized in design mode. Moving dots illustrate recurring activity on those connections, not measured packet counts or individual evidence records.

The Trace Adversarial Graph.

01

Communication traces

A lightweight kernel sensor records every process and connection, mapping normal and abnormal behavior in a live network graph.

02

AI Proxy

All model traffic passes through one gateway, ensuring no agent reaches inference without its traffic being captured.

03

Triage agents

Trace agents assess every anomaly to determine whether the behavior was intended, escalating only what wasn’t intended.

04

Trace code

Trace software behavior from development through deployment, tracing it back to the commit, author, agent, and prompt.

05

Adaptive sensors

Sensors adapt to your stack, collecting additional signals specific to how the systems in your environment actually run.

06

Adversarial approach

Collection is distributed across the network, so a silenced host is exposed by the neighboring systems still reporting it.

Threats we trace.

01

Directed agent

A person instructing an agent to act maliciously and carry out harmful actions on their behalf.

02

Insider

A person using their own trusted credentials to carry out malicious actions within a system.

03

Agent gone wrong

An agent pursuing a harmless request through unauthorized actions or illegitimate means.

04

External agent

An outside agent that has entered the network and is carrying out actions independently.

05

External human

An outside person who has entered the network and is carrying out actions at the keyboard.

06

Compromised model

A model with bias or instructions injected upstream into open or third-party weights.

07

Bad practices

Systems running with weak security practices that leave them vulnerable to malicious use.

The diagrams and source excerpts illustrate synthetic observations, not live telemetry. Two cases are explained; the dataset worker case needs human review. Independent relationships are not a correlated request trace.