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Analysis & spreadsheets35k · #5789

hunting-for-data-exfiltration-indicators

Helps your agent find signs of data theft by analyzing network traffic. Useful for detecting unusual data flows and suspicious cloud uploads.

What it does

This tool looks for signs of data theft on your network. It analyzes internet traffic to find suspicious activity, like large data uploads to unusual places or strange DNS usage.

When to use it

  • ✓When you suspect data has been stolen.
  • ✓If there's an unusual increase in data being sent out of the network.
  • ✓To investigate if someone inside the company is stealing information.

Example of what to ask your AI

“Hunt for data theft on our network.”

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/hunting-for-data-exfiltration-indicators/SKILL.md

Ready-to-paste message

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

It compares what's normal on your network with what's happening now. If something is very different, like a huge amount of data being sent to an unknown website, it raises an alert.

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 hunting-for-data-exfiltration-indicators

Or download just the file:

curl -L https://raw.githubusercontent.com/mukul975/Anthropic-Cybersecurity-Skills/main/skills/hunting-for-data-exfiltration-indicators/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Hunting for Data Exfiltration Indicators

When to Use

  • When hunting for data theft in compromised environments
  • After detecting unusual outbound data volumes or patterns
  • When investigating potential insider threat data theft
  • During incident response to determine what data was stolen
  • When threat intel indicates data exfiltration campaigns targeting your sector

Prerequisites

  • Network proxy/firewall logs with byte-level data transfer metrics
  • DLP solution or CASB with cloud upload visibility
  • DNS query logs for DNS exfiltration detection
  • Email gateway logs for attachment monitoring
  • SIEM with data volume anomaly detection capabilities

Workflow

  1. Define Exfiltration Channels: Identify potential channels (HTTP/S uploads, DNS tunneling, email attachments, cloud storage, removable media, encrypted protocols).
  2. Baseline Normal Data Flows: Establish baseline outbound data transfer volumes per user, host, and destination over a 30-day window.
  3. Detect Volume Anomalies: Identify hosts or users transferring significantly more data than baseline to external destinations.
  4. Analyze Transfer Destinations: Check destination domains/IPs against threat intel, identify newly registered domains, personal cloud storage, and foreign infrastructure.
  5. Inspect Protocol Abuse: Look for DNS tunneling (large/frequent TXT queries), ICMP tunneling, or data hidden in allowed protocols.
  6. Correlate with File Access: Link exfiltration indicators to file access events on sensitive file shares, databases, or repositories.
  7. Report and Contain: Document findings with evidence, estimate data exposure, and recommend containment actions.

Key Concepts

Concept Description
T1041 Exfiltration Over C2 Channel
T1048 Exfiltration Over Alternative Protocol
T1048.001 Exfiltration Over Symmetric Encrypted Non-C2
T1048.002 Exfiltration Over Asymmetric Encrypted Non-C2
T1048.003 Exfiltration Over Unencrypted/Obfuscated Non-C2
T1567 Exfiltration Over Web Service
T1567.002 Exfiltration to Cloud Storage
T1052 Exfiltration Over Physical Medium
T1029 Scheduled Transfer
T1030 Data Transfer Size Limits (staging)
T1537 Transfer Data to Cloud Account
T1020 Automated Exfiltration

Tools & Systems

Tool Purpose
Splunk SIEM for data volume analysis and SPL queries
Zeek Network metadata for data flow analysis
Microsoft Defender for Cloud Apps CASB for cloud exfiltration
Netskope Cloud DLP and exfiltration detection
Suricata Network IDS for protocol anomaly detection
RITA DNS exfiltration and beacon detection
ExtraHop Network traffic analysis for data flow

Common Scenarios

  1. Cloud Storage Exfiltration: User uploads sensitive documents to personal Google Drive or Dropbox via browser.
  2. DNS Tunneling: Malware exfiltrates data encoded in DNS subdomain queries to attacker-controlled nameserver.
  3. HTTPS Upload: Compromised system POSTs large data blobs to C2 server over encrypted HTTPS.
  4. Email Attachment Exfiltration: Insider forwards sensitive documents to personal email accounts.
  5. Staging and Compression: Adversary stages data in compressed archives before slow exfiltration to avoid detection.

Output Format

Hunt ID: TH-EXFIL-[DATE]-[SEQ]
Exfiltration Channel: [HTTP/DNS/Email/Cloud/USB]
Source: [Host/User]
Destination: [Domain/IP/Service]
Data Volume: [Bytes/MB/GB]
Time Period: [Start - End]
Protocol: [HTTPS/DNS/SMTP/SMB]
Files Involved: [Count/Types]
Risk Level: [Critical/High/Medium/Low]
Confidence: [High/Medium/Low]
FAQ

What are 'data exfiltration indicators'?

These are signals or patterns in network traffic that suggest data is being copied and sent out of the network without authorization.

What kind of suspicious data can it find?

It can find data being sent to personal cloud services, using DNS strangely to hide information, or large data volumes in general.

Do I need to install anything extra?

Yes, this tool works best when combined with other security tools that already monitor network logs, DNS, and cloud uploads.

Details

Original description by the author

Hunt for data exfiltration by analyzing Zeek and Suricata network telemetry for unusual data flows, DNS tunneling via large/frequent TXT queries, uploads to personal cloud storage, and encrypted-channel abuse, correlated against threat intel on destination domains. Use when hunting for data theft in a compromised environment, investigating unusual outbound data volumes, or determining what data wa

repo: mukul975/Anthropic-Cybersecurity-Skills

Popularity

GitHub stars
35k
Ranking position
#5789
License
Apache-2.0
Updated
8/31/2026

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