Build or tune a monitoring pipeline that learns normal user behavior from activity logs. Use Elasticsearch or OpenSearch to score unusual activity, compare colleagues in similar roles, and combine warning signs into insider threat alerts.
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Implement User and Entity Behavior Analytics (UEBA) using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and alert on insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access. Use when building or tuning a UEBA pipeline rather than a one-off manual hunt.
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User and Entity Behavior Analytics (UEBA) moves beyond static rule-based detection to model normal behavior for users, hosts, and applications, then flag statistically significant deviations that may indicate insider threats. Using Elasticsearch as the analytics backend, this skill covers building behavioral baselines from authentication logs, file access events, and network activity, computing risk scores using statistical deviation and peer group comparison, and correlating multiple low-confidence indicators into high-confidence insider threat alerts.
Configure log pipelines to ingest authentication, file access, email, and network logs into Elasticsearch with a unified user identity field.
Calculate per-user baselines for login times, data volume, application usage, and access patterns over a rolling 30-day window using Elasticsearch aggregations.
Compare current activity against baselines using z-score deviation and peer group comparison to generate per-user risk scores.
Combine multiple anomalous indicators (unusual hours + large downloads + new system access) into composite risk scores that trigger SOC investigation workflows.
JSON report containing per-user risk scores, anomalous activity details, peer group deviations, and recommended investigation actions.
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Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.
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Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.
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Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.
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Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.
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Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.
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Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.
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