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Agents35k · #5673

detecting-insider-threat-behaviors

Helps your agent find signs of insider threats, like strange data access or information theft by unhappy employees. Allows action before damage occurs.

What it does

This tool helps find suspicious employee behaviors that might indicate data theft or other malicious actions. It looks for unusual file access, activity outside normal hours, mass downloads, and permission abuse.

When to use it

  • ✓When you want to proactively search for suspicious employee activities.
  • ✓When there's suspicion an employee might be stealing information before leaving the company.
  • ✓When a security alert suggests a potential issue with an employee.

Example of what to ask your AI

“Look for employees accessing many files outside of work hours.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/detecting-insider-threat-behaviors/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/mukul975/Anthropic-Cybersecurity-Skills/blob/main/skills/detecting-insider-threat-behaviors/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool analyzes computer and network activity logs to identify unusual patterns. It compares what's happening against what's considered normal for each employee.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill detecting-insider-threat-behaviors

Or download just the file:

curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/detecting-insider-threat-behaviors/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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]
FAQ

What programs are needed to use this tool?

You need programs that monitor computer activity (like CrowdStrike or Microsoft Defender) and systems that store and analyze logs (like Splunk or Elastic).

What are 'behavioral indicators'?

These are warning signs that suggest something unusual or suspicious might be happening, such as an employee accessing data they shouldn't.

What happens if the tool finds something suspicious?

The tool generates a report detailing the activity, its risk level, and recommended actions, such as further investigation or security measures.

Details

Original description by the author

Detect insider threat behavioral indicators including unusual data access, off-hours activity, mass file downloads, privilege abuse, and resignation-correlated data theft. Use when proactively threat-hunting for malicious or negligent insider activity, or when investigating a departing or disgruntled employee for potential data theft.

repo: mukul975/Anthropic-Cybersecurity-Skills

Popularity

GitHub stars
35k
Ranking position
#5673
License
Apache-2.0
Updated
8/31/2026

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