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hunting-for-data-exfiltration-indicators

hunting-for-data-exfiltration-indicators

github.com/mukul975Security35.2k66 installsUpdated 8w ago
Repository

About hunting-for-data-exfiltration-indicators

A data-exfiltration hunting guide for security operations and incident response teams investigating potential data theft and its scope. Its workflow covers traffic baselining, anomalous transfers, destination analysis, protocol abuse, and file-access correlation.

Key features

  1. 01Define potential exfiltration channels
  2. 02Establish normal outbound traffic baselines
  3. 03Detect transfer-volume anomalies
  4. 04Analyze destinations and protocol abuse
  5. 05Correlate file access and document response

Use cases

  1. 01Investigate unusual outbound data volumes
  2. 02Hunt for DNS tunneling or cloud-storage exfiltration
  3. 03Assess data stolen during an incident

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/mukul975/anthropic-cybersecurity-skills --skill hunting-for-data-exfiltration-indicators

After installing, type/hunting-for-data-exfiltration-indicatorsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE
assets/
template.md
references/
api-reference.md
standards.md
workflows.md
scripts/
agent.py
process.py

Details

From the project README

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

ConceptDescription
T1041Exfiltration Over C2 Channel
T1048Exfiltration Over Alternative Protocol
T1048.001Exfiltration Over Symmetric Encrypted Non-C2
T1048.002Exfiltration Over Asymmetric Encrypted Non-C2
T1048.003Exfiltration Over Unencrypted/Obfuscated Non-C2
T1567Exfiltration Over Web Service
T1567.002Exfiltration to Cloud Storage
T1052Exfiltration Over Physical Medium
T1029Scheduled Transfer
T1030Data Transfer Size Limits (staging)
T1537Transfer Data to Cloud Account
T1020Automated Exfiltration

Tools & Systems

ToolPurpose
SplunkSIEM for data volume analysis and SPL queries
ZeekNetwork metadata for data flow analysis
Microsoft Defender for Cloud AppsCASB for cloud exfiltration
NetskopeCloud DLP and exfiltration detection
SuricataNetwork IDS for protocol anomaly detection
RITADNS exfiltration and beacon detection
ExtraHopNetwork 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]

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