CYBO Gen · AI generated network traffic

Generate the network. Train for the real one.

CYBO Gen generates synthetic traffic so realistic that trained SOC analysts cannot easily tell it from genuine enterprise activity.

Request a briefing

Built to mission requirements from Army Cyber, the Cyber Protection Brigade, and U.S. Cyber Command.

80+Quality score to deploy

MinutesTo build an exercise, not days

3Roles: operator, analyst, monitor

Scenario plain English

Attacker has initial foothold via phishing email.

Target environment: domain controller, file server, SQL server.

Goal: locate and exfiltrate HR salary data. Stage data before exfil.

Windows 11macOS 14Ubuntu 229 devices

01Describe02Generate03Fingerprint 04Human timing05Imperfections06Validate

Pre exercise validation

100Ready for deployment

packets: 68,995 over 287.7 seconds
checks: packet countdurationprotocol diversityTTL consistency

Deploy to exercise pass threshold 80+

Why it matters

Fake traffic trains the wrong instincts. Traditional generators produce predictable patterns: perfect timing, missing protocol quirks, no network errors. Trainees learn to filter them out. When defenders can dismiss traffic as test data, they build shortcuts instead of the skills real threats demand.

OS fingerprints

Every device behaves like the system it claims to be.

TCP options, window sizes, and TTL values match the operating system, validated against Windows, macOS, Ubuntu, iOS, and Android signatures.

Encrypted sessions

Browsers look like browsers.

TLS signatures and HTTP headers stay consistent with each browser, so nothing gives away a synthetic session.

Timing

Human think time, not machine perfect intervals.

Delays follow models of real human behavior, down to network latency.

Network behavior

Real networks are imperfect. So is this one.

Retransmits, duplicate acknowledgments, and out of order packets appear at realistic rates, inside complete sessions with real payload sizes.

How it works

An adversary built in. An AI discriminator tests generated traffic against real captures and finds what gives it away, so the generator fixes it before your analysts ever see it.

Generate traffic

A scenario in plain English becomes a full packet capture, with device, browser, and role profiles applied.

Extract features

Timing distributions, TCP characteristics, and flow statistics are measured from real and generated traffic.

Train the discriminator

A classifier learns to tell real traffic from synthetic.

Find the tells

Feature importance shows exactly which signals give synthetic traffic away.

Fix them

The generator improves against the top signals, then the loop runs again.

Score before deploy

Every exercise is scored before it ships. Only traffic that passes the threshold reaches a trainee.

Three roles

Build it. Work it. Watch it. One exercise, three seats, every action on record.

The operator

Build exercises in minutes, not days.

Describe a scenario in plain English, pick role based profiles from developer to insider threat, inject attack indicators, validate before deploy, and stream live traffic to a cyber range.

The analyst

Train on production like traffic.

Inspect packets, decode protocols, follow flows and timelines, and find indicators embedded naturally in the traffic. Skills that transfer to SOC workflows, without live system risk.

The monitor

Know who is production ready.

Watch every analyst session live, see investigated versus missed traffic, send hints without giving answers, and export a debrief with Explainable AI insight into how the traffic was generated.

The family