hunting-for-data-exfiltration-indicators

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Hunt for data exfiltration through network traffic analysis, detecting unusual data flows, DNS tunneling, cloud storage uploads, and encrypted channel abuse.

AI & Automation 12,642 stars 1468 forks Updated today Apache-2.0

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Skill Content

# 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 t...

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Author
mukul975
Repository
mukul975/Anthropic-Cybersecurity-Skills
Created
3 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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