Detect Stealthy
Network Attacks
Built from first principles. Detects subtle signs of breach. Delivered as a service.
Cyber Spend Annually
$0B
YET
0+
Ransomware
Attacks Daily
The Problem
The industry still treats cybersecurity as a general problem—build comprehensive stacks that detect everything. The result is overwhelming noise while ransomware attacks continue undetected.
We explored how to solve this from first principles.
Network Attacks Happen Over the Network
And successful attacks always do these activities...
DAY 1-21
Command & Control
After breach, attackers establish persistent communication channels using legitimate protocols—Slack, DNS, HTTPS—to maintain stealth.
Traditional tools: See outbound traffic to legitimate enterprise targets.
Prophet: Detects Slack shift from human to programmatic beaconing pattern.
DAY 40-60
Data Exfiltration
Attackers steal data before deploying ransomware for double extortion. They're patient and stealthy, slowly leaking data to legitimate services over extended periods.
Traditional tools: See a 100MB upload to Google Drive during business hours.
Prophet: Sees 100MB uploaded to Google Drive over the last 40 hours from a server.
Purpose-built post-breach detection using network traffic
Networks Are Everywhere
And they produce a lot of traffic...
SEE EVERYTHING
Detect Network-Wide
Advanced attacks coordinate across infrastructure. Detecting them requires observing behavior network-wide, not analyzing traffic in isolation.
Traditional tools: Independent appliances. Local visibility only.
Prophet: Unified platform. Global network view. Lightweight collectors deployed anywhere.
REMEMBER EVERYTHING
Detect Over Time
Detecting slow exfiltration and long-running C2 requires several days of context—for AI inference, sub-second search, and forensic investigation.
Traditional NDR: Real-time only or slow queries. Not both.
Prophet: 6 months retention. Sub-second queries. Week-long AI context windows.
Complete visibility, long-term memory
AI Must Understand Network Physics
And learn what attacks actually look like...
LEARN FUNDAMENTALS
Detect Subtle Behavioral Patterns
Advanced attacks hide in subtle patterns—timing, volume curves, protocol sequences. Signatures miss these nuances. Detection requires understanding packet physics, not matching known patterns.
Traditional tools: Match signatures. Miss subtle deviations.
Prophet: Foundation model. Detects subtle behavioral anomalies in packet sequences.
LEARN ATTACKS
Distinguish Attacks from Anomalies
Attackers exploit the ambiguity of anomaly detection. They mimic legitimate patterns—backups, maintenance, sync operations—while executing C2 and exfiltration. Models trained only on "normal" flag everything unusual, overwhelming teams. Detection requires learning adversary tradecraft.
Traditional tools: Detect statistical deviations. Alert on every anomaly.
Prophet: Trained on both legitimate and malicious traffic. Low false positive rate.
Transformer AI analyzing all traffic
Deploy Prophet
ONE
Create Account
Portal generates deployment token. No sales calls.
TWO
Deploy Collector
Docker or binary. Streams metadata to Prophet cloud.
docker run prophetic/collector --token=<token>
./prophet_collector --token=<token>
Binary runs on Windows, Linux, any OS.
THREE
Configure Alerts
Prophet UI, Slack, webhook, SIEM integration.
Configure in portal.
