detecting-insider-threat-behaviors
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npx mdskill add mukul975/Anthropic-Cybersecurity-Skills/detecting-insider-threat-behaviorsHunt insider threats by analyzing behavioral anomalies and access patterns.
- Identifies suspicious data access, off-hours activity, and mass downloads.
- Integrates with EDR, SIEM, Sysmon, and Windows Security logs.
- Correlates telemetry against threat intelligence and ATT&CK frameworks.
- Generates actionable alerts for security teams during investigations.
SKILL.md
.github/skills/detecting-insider-threat-behaviorsView on GitHub ↗
--- name: detecting-insider-threat-behaviors description: Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft. domain: cybersecurity subdomain: threat-hunting tags: [threat-hunting, mitre-attack, insider-threat, data-theft, ueba, proactive-detection] version: "1.0" author: mahipal license: Apache-2.0 --- # Detecting Insider Threat Behaviors ## When to Use - When proactively hunting for indicators of detecting insider threat behaviors in the environment - After threat intelligence indicates active campaigns using these techniques - During incident response to scope compromise related to these techniques - When EDR or SIEM alerts trigger on related indicators - During periodic security assessments and purple team exercises ## Prerequisites - EDR platform with process and network telemetry (CrowdStrike, MDE, SentinelOne) - SIEM with relevant log data ingested (Splunk, Elastic, Sentinel) - Sysmon deployed with comprehensive configuration - Windows Security Event Log forwarding enabled - Threat intelligence feeds for IOC correlation ## Workflow 1. **Formulate Hypothesis**: Define a testable hypothesis based on threat intelligence or ATT&CK gap analysis. 2. **Identify Data Sources**: Determine which logs and telemetry are needed to validate or refute the hypothesis. 3. **Execute Queries**: Run detection queries against SIEM and EDR platforms to collect relevant events. 4. **Analyze Results**: Examine query results for anomalies, correlating across multiple data sources. 5. **Validate Findings**: Distinguish true positives from false positives through contextual analysis. 6. **Correlate Activity**: Link findings to broader attack chains and threat actor TTPs. 7. **Document and Report**: Record findings, update detection rules, and recommend response actions. ## Key Concepts | Concept | Description | |---------|-------------| | T1078 | Valid Accounts | | T1530 | Data from Cloud Storage Object | | T1567 | Exfiltration Over Web Service | ## Tools & Systems | Tool | Purpose | |------|---------| | CrowdStrike Falcon | EDR telemetry and threat detection | | Microsoft Defender for Endpoint | Advanced hunting with KQL | | Splunk Enterprise | SIEM log analysis with SPL queries | | Elastic Security | Detection rules and investigation timeline | | Sysmon | Detailed Windows event monitoring | | Velociraptor | Endpoint artifact collection and hunting | | Sigma Rules | Cross-platform detection rule format | ## Common Scenarios 1. **Scenario 1**: Employee downloading bulk files before resignation 2. **Scenario 2**: IT admin accessing HR data outside job function 3. **Scenario 3**: Service account used for unauthorized data queries 4. **Scenario 4**: Contractor copying source code to personal cloud storage ## Output Format ``` Hunt ID: TH-DETECT-[DATE]-[SEQ] Technique: T1078 Host: [Hostname] User: [Account context] Evidence: [Log entries, process trees, network data] Risk Level: [Critical/High/Medium/Low] Confidence: [High/Medium/Low] Recommended Action: [Containment, investigation, monitoring] ```