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Cyera has launched Omni DLP, an AI-native, real-time data loss prevention (DLP) solution designed to address the long-standing inefficiencies in traditional DLP systems. Unlike legacy tools that generate excessive noise and false positives, Omni DLP leverages AI to classify data accurately, reduce alerts, and protect data across all states—at rest, in motion, and in use, including AI platforms like Copilot and ChatGPT.
🔗 Read more: Omni DLP by Cyera
You Should Know: Key Features & Technical Implementation
1. AI-Native Data Classification
Omni DLP integrates Cyera’s AI-driven data classification engine to:
– Automatically identify sensitive data (PII, PCI, PHI).
– Reduce manual tagging errors.
– Apply context-aware policies.
Example Command (Linux – Data Scanning with `grep`):
grep -r --include=".txt" "SSN=[0-9]{3}-[0-9]{2}-[0-9]{4}" /var/data/
Scans for Social Security Numbers in text files.
- Real-Time Data Protection (Inspired by Trail Security)
Omni DLP monitors data flows in real-time, blocking unauthorized transfers.
Example (Windows – Monitor Network Traffic with PowerShell):
Get-NetTCPConnection -State Established | Where-Object { $_.RemotePort -eq 443 } | Format-Table -AutoSize
Checks active HTTPS connections for potential exfiltration.
3. Noise Reduction with AI-Powered Alerting
Legacy DLP tools flood analysts with alerts. Omni DLP filters false positives using:
– Behavioral analysis.
– User activity baselines.
Example (Linux – Log Analysis with `journalctl`):
journalctl -u sshd --since "1 hour ago" | grep "Failed password"
Filters SSH brute-force attempts.
4. Protecting AI Systems (ChatGPT, Copilot)
Omni DLP extends protection to AI tools by:
- Detecting sensitive data in prompts/responses.
- Enforcing redaction policies.
Example (Python – Text Redaction Script):
import re
text = "User SSN: 123-45-6789"
redacted = re.sub(r"\d{3}-\d{2}-\d{4}", "[REDACTED-SSN]", text)
print(redacted)
Automatically masks SSNs in text.
What Undercode Say
Omni DLP represents a paradigm shift in cybersecurity, replacing outdated, rule-based DLP with AI-driven precision. Key takeaways:
– For Linux Admins: Use `auditd` to track file access:
sudo auditctl -w /etc/passwd -p rwa -k sensitive_file_access
– For Windows SecOps: Deploy Windows Defender DLP:
Set-MpPreference -EnableNetworkProtection Enabled
– For Cloud Teams: Integrate with AWS Macie or Azure Purview for automated data labeling.
The future of DLP is real-time, AI-powered, and actionable—Cyera’s Omni DLP is leading the charge.
Expected Output:
A 70-line technical deep dive into Omni DLP’s AI-driven approach, featuring Linux/Windows commands, log analysis, and redaction scripts for cybersecurity professionals.
🔗 Reference: Cyera Omni DLP Blog
References:
Reported By: Yotam Segev – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅
