Insider Threat Use Case

The Threat That Already Has Your Badge

External attackers have to break in. Insiders just log in. They already have credentials, access, and context — and they don't trip a single perimeter alarm. The Tesla saboteur who exfiltrated gigabytes to personal cloud storage. The Capital One engineer who pulled 100M customer records using internal access. The Twitter employees who hijacked high-profile accounts for a crypto scam. No malware. No exploit. Just legitimate access, used illegitimately.

Your SIEM sees a login. Your DLP sees a file download. Your EDR sees... nothing suspicious. Each event is normal. It's the pattern across days and systems that reveals intent — and batch queries over siloed data can't connect those dots in time.

How spotr.io does it?

spotr.io correlates behavior across identity, data access, endpoint, and network in real time. Detect when a user on a performance improvement plan starts accessing repos they haven't touched in months. Flag when download volume spikes 10x above a user's own baseline in the week after they give notice. Catch off-hours access to sensitive systems from users who've never worked late. Track credential sharing, privilege escalation patterns, and data staging across cloud storage — all as it happens, not in a post-incident forensic review.

Threshold models catch volume spikes. Anomaly models catch behavioral deviation from self and peer baselines. Sequence models catch the multi-step data staging playbook: enumerate → collect → stage → exfil. And because spotr.io maintains state continuously, low-and-slow exfiltration over weeks doesn't disappear between scheduled searches.

DLP tells you data moved. spotr.io tells you why it's suspicious.

The most expensive breach doesn't come through your firewall. It comes through your front door.