Automated Phishing and Insider Threat Detection

Large campuses and education providers support thousands of students, faculty, and contractors using varied devices and cloud apps; constrained IT/security budgets and noisy alert streams create long detection times and missed account compromises. Phishing and credential theft are common vectors, and manual triage of every alert overwhelms small SOC teams, increasing time-to-contain and risk to sensitive student and research data.

Combine machine learning on multi-source telemetry with deterministic rules and a human-in-the-loop SOAR workflow to detect and act on phishing and insider indicators. Models run continuously to score events and group related activity, while playbooks automate containment for high-confidence cases and route ambiguous cases to analysts with explainable evidence. Privacy and compliance controls limit sensitive data access and logging, and analyst feedback retrains models to reduce false positives.

• Ingest: M365/Google Workspace logs, email metadata and attachments, SSO/authentication logs, VPN/EDR telemetry, and mailbox forwarding/forwarder rules.
• Detection: use NLP classifiers for spearphishing indicators, graph-based user-behavior baselining for lateral or anomalous access, and unsupervised clustering to group correlated alerts.
• Response: SOAR playbooks that auto-block malicious senders, revoke sessions, quarantine endpoints for high-confidence incidents, and create analyst tickets for medium-confidence cases with an evidence summary.
• Human-in-the-loop & governance: analyst review UI with explainable model signals, feedback loop for retraining, role-based access, FERPA-aware data minimization, and retention policies.

Teams typically see faster detection and lower analyst workload: illustrative results include 40-70% reduction in manual triage volume, 30-60% fewer false positives routed to investigators, and median time-to-contain moving from days to hours for high-confidence incidents. Financially, a mid-sized institution can expect lower incident response costs and avoided compromise losses (illustratively tens to hundreds of thousands USD annually) depending on scale and prior breach frequency.