Adversary observation infrastructure · 2026
We deploy deception sensors in the wild and extract structured behavioral intelligence from live adversary interactions — before the intrusion happens.
Architecture
Five stages — fully automated, zero synthetic data.
Deception sensors
Distributed honeypots
exposing realistic attack surfaces
Ingest pipeline
NATS JetStream
high-throughput streaming
Cognition engine
Behavioral extraction
+ TTP classification
Intel API
REST · JSON
Structured delivery
Your workflows
SIEM · TIP · XDR
Direct integration
Data assets
Structured intelligence objects — not raw logs.
Per-session record
Full interaction timeline — ports, payloads, timing, protocol fingerprint, exploit attempts sequenced.
Per-actor profile
Attributed behavioral cluster — ASN, campaign, tooling inferred from behavioral convergence across sessions.
Per-IP intelligence
Enriched IP object — threat score, observed TTPs, last seen, country, historical behavior, reputation history.
Temporal signals
Attack wave detection — time-series aggregation across sensors, pre-intrusion surge identification by technique.
Delivery & integration
Pull or push — REST API with filtering, webhook streaming, or scheduled STIX bundle drops. Schema-stable, versioned, documented. Compatible with any security stack that speaks HTTP.
Differentiation
Every data point captured by sensors we operate. No third-party feed, no recycled labels.
| Capability | HeXG | Recorded Future | Sekoia.io | GreyNoise |
|---|---|---|---|---|
| Primary behavioral data | ✓ | ✗ | ✗ | partial |
| Pre-intrusion signals | ✓ | ✗ | ✗ | partial |
| Attacker intent classification | ✓ | partial | partial | ✗ |
| Session-level behavioral depth | ✓ | ✗ | ✗ | ✗ |
| No cloud data dependency | ✓ | ✗ | ✗ | ✗ |
We work with a small number of security teams. If the signal matters to your work, let's talk.
Get in touch →