What data sources are required for this analysis?

The skill is designed to process endpoint activity logs, cloud storage access logs, and email DLP event files, typically in CSV format.

Can I use this for real-time monitoring?

While the skill provides the logic and code for detection, it is primarily intended for investigation or as a template for building automated rules in a SIEM or monitoring platform.

What technical prerequisites are needed?

You will need Python 3.8+ and the pandas library installed to execute the behavioral analytics scripts provided by this skill.

How does this skill detect anomalies?

It uses Python's pandas library to calculate a statistical baseline of historical user activity and flags events that significantly deviate, such as uploads exceeding 3x the daily average.

Insider Data Exfiltration Detection

Name: Insider Data Exfiltration Detection
Author: micsapp

bymicsapp

0•

Security & Testing

Identifies unauthorized data movement by analyzing DLP logs and user behavior patterns using statistical anomaly detection.

This skill empowers security professionals to detect potential data theft by internal actors through the analysis of Data Loss Prevention (DLP) alerts and endpoint activity. By leveraging Python-based behavioral analytics, it establishes statistical baselines for file access and upload volumes to highlight anomalies such as bulk downloads, off-hours activity, and excessive external transfers. It is particularly valuable for SOC analysts conducting forensic investigations or building automated threat-hunting queries to mitigate insider risk and improve data loss prevention strategies.

Key Features

01Analysis of endpoint activity and cloud storage logs

02Detection logic for bulk downloads and USB device usage

03Anomaly detection for volume spikes exceeding 3x averages

04Statistical behavioral baselines for user upload volumes

05Automated identification of off-hours file access patterns

060 GitHub stars

Use Cases

01Validating security monitoring coverage for insider threat attack techniques

02Investigating security incidents involving suspicious employee data access

03Developing automated threat hunting queries for SOC environments

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add micsapp/micstec-skills detecting-insider-data-exfiltration-via-dlp

For use in Claude.ai and ChatGPT

Key Features

01Analysis of endpoint activity and cloud storage logs

02Detection logic for bulk downloads and USB device usage

03Anomaly detection for volume spikes exceeding 3x averages

04Statistical behavioral baselines for user upload volumes

05Automated identification of off-hours file access patterns

060 GitHub stars

Use Cases

01Validating security monitoring coverage for insider threat attack techniques

02Investigating security incidents involving suspicious employee data access

03Developing automated threat hunting queries for SOC environments

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add micsapp/micstec-skills detecting-insider-data-exfiltration-via-dlp

For use in Claude.ai and ChatGPT