Prioritised, actionable alerting across cloud, endpoint, identity, network and SaaS, with 2,000+ managed detections, behavioural analytics and threat intelligence applied automatically to every signal.
2,000+ managed detections, behavioural analytics and threat intelligence operate from the first connected source, with kill-chain scoring consolidating signals into prioritised threats.
Coverage across cloud, endpoint, identity, network and SaaS, written, tuned and maintained by Secure60, with new content released continuously and no detection engineering required from the customer.
Behavioural baselines for every user and host, with statistical models covering what rules cannot anticipate — outliers in volume, timing, geography and behaviour.
IP and domain reputation and malicious-traffic feeds are matched against every signal at write time, without a separate console or manual lookup. Dark-web monitoring is available as an add-on.
Signals cluster by entity and kill-chain phase and are scored with intelligence context, so triage begins at the threat rather than at the individual alert.
Auth log, EDR telemetry, cloud audit trail
2,000+ rules, behavioural baselines, anomaly models
Enriched with IP, domain and threat intelligence
Clustered by entity and kill-chain phase, then scored
Signals cluster into scored threats with intelligence context attached, enabling direct pivot to the entity and its timeline.
2,000+ curated detections arrive tested against production data, with custom detections authored on top of them.
A single risk picture covering threats, posture and audit evidence in one console.
Every signal the SIEM raises propagates into the rest of the platform on the same entities, timeline and console.
Every event the SIEM scores is the same event Log Management retained, on a single ingestion and a single schema.
A signal on a host carries that host's known vulnerabilities, providing exposure context at the point of triage.
Detected threats become control evidence, with coverage reporting on which controls fired and where.
AI-specific detections run in the same pipeline — prompt injection, shadow AI and anomalous model calls.
