Tuned per tenant
No generic playbook library - rules and ML models tuned against each customer's baseline and operational reality.
Detection content engineered against your environment, your telemetry and the adversaries that target your sector.
A detection engineering practice built on the Helios AI/ML Suite and Vectra's APAC threat library. We build, tune and maintain the rules and ML models that fire in your SIEM or XDR, against the telemetry you actually collect and the adversaries that actually target you.
We start with a coverage gap assessment against your telemetry and threat profile, prioritise the gaps that matter, then build, test and operate detection content against them - with measurable false-positive and dwell-time targets.
No generic playbook library - rules and ML models tuned against each customer's baseline and operational reality.
Coverage mapped to ATT&CK and to the campaigns we have observed this quarter against your sector.
Detection content reviewed against drift and false-positive rate as the estate changes - not set-and-forget.
ML models for the behaviours rules cannot catch, with reasoning and evidence attached to each detection.
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