Your Data Loss Prevention (DLP) system flagged unusual outbound traffic from database server (db-prod-01) at 22:45 UTC on November 28, 2025. Network monitoring shows a large data transfer (2.3 GB) to an unknown external IP address. Your mission is to analyze system logs, command history, and network activity to determine what data was exfiltrated and how.
Data exfiltration is the unauthorized transfer of data from a computer system. Attackers typically compress, encrypt, and stage data before transferring it to external servers to avoid detection.
Direct Transfer: SCP, SFTP, FTP, rsync to attacker-controlled servers
Encrypted Channels: HTTPS uploads, SSH tunnels, VPNs
Cloud Storage: Upload to Dropbox, Google Drive, AWS S3
Covert Channels: DNS tunneling, ICMP tunneling, steganography
1. Discovery: Locate valuable data (databases, credentials, PII)
2. Staging: Copy data to temporary location (/tmp, /dev/shm)
3. Compression: tar, gzip, zip to reduce size
4. Encryption (Optional): Encrypt archive to avoid DLP detection
5. Transfer: Send to external server via SCP, curl, nc
6. Cleanup: Delete staging files to hide traces
Command History: tar, gzip, scp, curl to external IPs
Network Traffic: Large outbound transfers, connections to unknown IPs
File System: Large archives in /tmp, recent file modifications
Process Activity: tar/gzip processes, network tools running
๐ก Defense Tip: Implement DLP solutions, monitor outbound traffic for anomalies, enforce egress filtering, use network segmentation, and maintain command/file integrity monitoring (FIM).
Run bash commands to analyze the logs. Available: cat, grep, wc, awk, netstat, find, ls, clear, help
This section auto-fills once all tasks are completed correctly.
Complete all tasks to reveal the exfiltration chain.
The data exfiltration succeeded because:
1. Database admin account had unrestricted outbound network access
2. No egress filtering or DLP inspection for SSH/SCP traffic
3. No alerting on large mysqldump operations or file transfers
4. Attacker had compromised credentials with database access
5. Lack of database activity monitoring and anomaly detection