Look-alike domains, leaked credentials and AI-reputation risk — the outside-in exposure traditional monitoring can't see, watched continuously and worked in the same queue as everything else.
Every other capability watches telemetry you send in. Digital Risk Protection watches the attack surface you don't control — domains standing up to impersonate you, credentials surfacing in breach data, and how your brand is represented in AI answers. None of it touches your logs, so a SIEM alone never sees it.
Typosquats and homoglyph domains registered to impersonate you — flagged the moment they stand up, before the phishing starts.
Credentials tied to your domains surfacing in breach and stealer-log data, so you can force resets before they're used.
How the major AI models answer questions about your brand — catching false, damaging or reputation-shaping claims as a security and governance risk, not a marketing metric.
High and medium findings become managed threats in your normal queue — triaged by your agents, assigned to owners, and governed like any other threat.
Your domains and brands, continuously
Mail · hosting · cert · registration age
High / medium findings become threats
Triage, assign and close in the queue
One row per brand or asset — the look-alike domains found, credential and AI-reputation exposure, open threats, and what that exposure is worth to your organisation.
See the impersonation and exposure a SIEM can't, without standing up a separate digital-risk console — it lands in the queue you already work.
Catch look-alike domains and false AI claims early, with the evidence to act — takedown prep, resets, or a benign call you can record.
External exposure as a number you can show the board, tuned to what an attack actually costs your organisation.
External risk doesn't sit in its own silo. It becomes a threat like any other, feeds the same triage and response, and evidences the controls that prove you're watching beyond the perimeter.
Detections are written to the same context as your logs, so external findings sit alongside everything else you collect.
High-risk findings are promoted to managed threats and triaged next to your internal detections — one queue, one operating model.
Monitoring the external attack surface is itself a control — the evidence that you're watching beyond the perimeter is collected automatically.
AI-reputation monitoring runs on the same governed models you use elsewhere — brand risk in AI answers, watched and audited.
