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Real-Time Anomaly Detection for Complex Networks

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Supervised vs. Unsupervised ML

Supervised ML models detect what’s known. Cyntros goes beyond that. Using unsupervised learning, it ingests high-velocity network traffic, continuously models normal system behavior, and flags deviations immediately- without relying on rules, labeled training data, or predefined indicators of compromise (IOCs).

  • No dependency on Known Threats
  • Zero-Day Threat Detection
  • High-Volume Traffic Analysis

How It Works

Behavioral Modeling

Data Integration

Alerting & Visualization

Why Teams Choose Cyntros

Detects What Other Tools Miss

Works Out of the Box

Cuts Through the Noise

Fits Into Your Stack

Proven Results

95

of malicious network activity detected

for attacks missed by top security vendors including CrowdStrike, Microsoft, SentinelOne, BitDefender, ESET, and Sophos.¹

97

effective against CISA KEV network exploits

Cyntros outperformed real-world threats cataloged by the Cybersecurity & Infrastructure Security Agency (CISA).¹

0

zero disruption

Cyntros runs passively on mirrored traffic, integrating seamlessly with your stack — no interference, no gaps, no compromise to data flow or operations.

¹ Source: Cyntros Network Detection and Response Evaluation conducted by Miercom, an independent test lab – July 2025.

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