Anomaly detection
Catch what rules and signatures can't see.
Modern attacks often don't use known malware. An attacker logs in with stolen credentials, moves through the network like a regular user and exfiltrates data slowly and quietly. That's why anomaly detection doesn't just look for known patterns – it looks for deviations from normal behaviour.
How it works
- we collect data on network traffic and on the behaviour of users, devices and applications
- this builds a picture of what normal looks like in your environment
- the system flags anomalies – a login at an odd hour, a new communication pattern or an unexpected volume of data leaving the network
- every alert comes with context, so you can quickly tell whether it is a real threat
What it can uncover
- misused or compromised accounts
- attackers moving laterally inside the network
- data leaks and unauthorised transfers
- infected devices communicating with an attacker
- misconfigurations and unexpected changes in traffic
What you get
- early warning of attacks, even those with no known signature
- visibility into what is really happening on your network
- fewer blind spots that your other security tools don't cover
AI
AI in practice: Machine-learning models learn what normal traffic looks like and flag deviations that fixed rules would miss.
Who it's for: organisations whose data and operations are a target and who need to see beyond the network perimeter.
