AGENT SKILL

detecting-insider-threat-behaviors

Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.

License 许可
Apache-2.0
最近更新
2026-11-14
Stars
★ 13
Forks
2

01 前言 Front Matter

name
detecting-insider-threat-behaviors
tags
[ "threat-hunting", "mitre-attack", "insider-threat", "data-theft", "ueba", "proactive-detection" ]
author
mahipal
domain
cybersecurity
source
https://github.com/mukul975/Anthropic-Cybersecurity-Skills
license
Apache-2.0
version
1.0
nist_csf
[ "DE.CM-01", "DE.AE-02", "DE.AE-07", "ID.RA-05" ]
subdomain
threat-hunting
description
Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft.
mitre_attack
[ "T1046", "T1057", "T1082", "T1083" ]
source_commit
04450304b12645cb2b974ab96d28c0664758a88d
d3fend_techniques
[ "Restore Access", "Password Authentication", "Biometric Authentication", "Strong Password Policy", "Restore User Account Access" ]

02 资源文件 7

03 SKILL.md 正文

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]

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