Threat Detection That Doesn't Sleep
CyberAgent orchestrates a swarm of autonomous MageAgent instances to hunt threats across your entire infrastructure — correlating signals from endpoint, network, cloud, and identity in real time.
What CyberAgent Does
Four foundational capabilities that make autonomous security operations possible at enterprise scale.
Autonomous Threat Hunting
Persistent MageAgent sub-agents continuously hunt for indicators of compromise without waiting for alerts. Hypotheses are generated, tested, and closed — automatically — across endpoint, network, and cloud telemetry.
Cross-Domain Correlation
GraphRAG links signals across endpoint, network, cloud, and identity layers in under 100ms. A single compromised credential becomes a full kill-chain graph — not a pile of unrelated alerts.
Sandbox Execution
Suspicious payloads, scripts, and binaries are detonated inside isolated MageAgent sandboxes. Behavioral analysis runs in parallel — file system mutations, network calls, and registry changes all captured and attributed.
Predictive Detection
Historical attack patterns stored in GraphRAG train a predictive layer that flags attack-precursor behaviors before the first exploit fires. 82% of confirmed threats were flagged at the reconnaissance stage.
Three Layers, One Response
CyberAgent is not a ruleset engine. It is a structured hierarchy of autonomous agents that reason, adapt, and act.
Orchestration Layer
A single CyberAgent coordinator receives enriched telemetry, forms threat hypotheses, and dispatches specialized sub-agents. It owns the investigation timeline and synthesizes findings into a single incident record.
- Hypothesis generation
- Sub-agent dispatch
- Incident synthesis
- Escalation decisions
Execution Layer
Independent MageAgent instances execute specific hunting tasks in parallel — each operating on a scoped view of telemetry. Results flow back to the coordinator with full reasoning chains attached.
- Parallel hunting jobs
- Tool-augmented reasoning
- Scoped telemetry access
- Reasoning chain export
Knowledge Layer
Every alert, entity, relationship, and resolved incident is written to a live knowledge graph. Sub-agents query it in under 100ms — so each new investigation starts with the full context of everything that came before.
- <100ms graph queries
- Entity relationship mapping
- Attack-pattern memory
- Cross-incident linking
56–68× Faster Than Legacy SOAR
Measured against real-world incident response times on equivalent alert volumes.
| Platform | Mean Time to Detect | Mean Time to Respond | False Positive Rate |
|---|---|---|---|
| CyberAgentAdverant | 45 seconds | < 3 minutes | < 6% |
| Splunk SOAR | ~45 minutes | ~3 hours | ~60% |
| Palo Alto XSOAR | ~40 minutes | ~2.5 hours | ~55% |
| Microsoft Sentinel | ~50 minutes | ~4 hours | ~65% |
Access Control Built In
CyberAgent runs on the same hardened platform that protects your customers — every action requires authentication, every decision is logged.
Protect Your Infrastructure
See CyberAgent eliminate alert fatigue and surface real threats in a live demo against your telemetry.