Trellix (formerly McAfee Enterprise) is a leading security platform provider, offering solutions such as Trellix ePolicy Orchestrator (ePO) and Enterprise DLP to help organizations protect sensitive information across endpoints, networks, and the cloud. Despite its powerful detection and prevention engines, false positives can still overwhelm security teams, forcing them to sift through piles of alerts—many of which turn out to be benign.
Strac has a radical new approach: a powerful browser extension that uses AI/ML and OCR to auto-classify DLP incidents as likely true positives or false positives—all within the Trellix DLP interface. Let’s walk through how it works and why it’s a game-changer.
1. The False Positive Challenge
Trellix (McAfee) Enterprise DLP is equipped with robust detection capabilities that can identify sensitive data (e.g., PCI, PII, HIPAA-regulated info) across email, endpoints, and network traffic. Yet DLP systems, no matter how advanced, may over-alert for a variety of reasons:
- Multiple matches that appear valid but lack real context (e.g., random numbers that happen to resemble social security numbers).
- Business processes that legitimately use what looks like sensitive data.
- Images or scanned documents where pattern recognition can trigger on partial text with no contextual cues.
The result: DLP teams find themselves triaging hundreds or thousands of incidents daily—most of which do not pose a real threat. Strac steps in to reduce the noise.
2. Strac’s Browser Extension
Embedded Intelligence
Strac’s browser extension is designed to function seamlessly with Trellix ePolicy Orchestrator (ePO)—the central management console for Trellix (McAfee) Enterprise DLP. Once installed:
- AI-Driven Triage: Every DLP incident that appears in Trellix ePO is automatically analyzed by Strac’s advanced ML models.
- False Positive Detection: The extension uses a combination of contextual AI and OCR to detect real exposures vs. innocuous data matches, drastically reducing false positives.
- In-Console Insights: It overlays classification or confidence scores directly in the Trellix DLP incident views, so you never need to switch tabs or log into a separate dashboard.
OCR & Contextual ML
Many DLP alerts involve attachments, images, or PDFs. Strac’s OCR capabilities convert images to text and feed it into the AI/ML pipeline, preserving business context (sender, recipient, domain trust, relevant keywords, etc.) to differentiate legitimate usage from policy violations.
3. Trellix + Strac Integration Flow
- Incident Generation: Trellix (McAfee) Enterprise DLP flags potential data security incidents (e.g., policy violation events) from endpoints, emails, or other channels.
- Incidents in ePO Console: These incidents appear in the Trellix ePolicy Orchestrator (ePO) interface, typically under the DLP Incident Manager.
- Strac Extension Activates: When an analyst navigates to the Incident Manager in ePO, Strac recognizes the active DLP alerts on the page.
- AI Analysis: Strac’s AI engine retrieves relevant incident details—policy triggers, message body, attachments—and processes them for advanced classification.
- Auto-Triage & Scoring: Strac assigns a Strac Risk Score—ranging from “Low (Likely FP)” to “High (Likely TP)”—directly visible in the incident table or incident details pane.
- Analyst Action: Based on Strac’s classification, security analysts can prioritize or bulk-resolve incidents, focusing their energy on genuine threats.
4. Why This Matters for Your Security Team
- Significant Time Savings
- By sorting out the likely false positives, Strac slashes the manual review burden, letting your analysts concentrate on the real threats.
- Native-Like User Experience
- You don’t have to jump between multiple products or dashboards—Strac works right where you already manage incidents: Trellix ePO.
- Context-Rich Detection
- Strac’s AI/ML goes beyond standard regex or pattern-based detections. It integrates contextual user data, message content, and real-time OCR to sharpen classification.
- Improved Security Posture
- By reducing noise, you free up resources to investigate genuine breaches or policy violations more thoroughly.
5. Deployment & Setup
Getting started with Strac is straightforward:
- Install the Browser Extension: Deploy the Strac extension to analyst workstations or through a corporate extension store.
- Configure Permissions: The extension securely accesses relevant incident data within Trellix ePO, typically requiring read-only or read/write permissions.
- AI Training (Optional): Enhance Strac’s accuracy by feeding it historical DLP incidents from your environment, fine-tuning the ML models.
- Seamless Workflow: Once configured, Strac’s insights automatically appear in Trellix ePO whenever you view incidents.
No major infrastructural overhaul, minimal operational overhead—just a synergy of Trellix + Strac.
6. FAQs
- How does Strac affect Trellix DLP performance?
- Strac functions independently as a browser extension with lightweight integration to the cloud-based AI engine. It doesn’t impact the core performance of Trellix ePO or your DLP endpoints.
- Will Strac interfere with Trellix’s existing DLP workflows or policies?
- Not at all. Strac is additive, providing risk scores and classifications that complement Trellix’s existing detection rules. You can still run your typical DLP workflows, auto-remediation policies, or escalations through Trellix ePO.
- Is our sensitive data secure?
- Yes, Strac employs stringent encryption and data anonymization practices. Only minimal, relevant metadata is processed to determine risk scores—ensuring compliance with internal and external data privacy requirements.
- Does Strac support older McAfee-branded releases?
- Strac strives for broad compatibility, including support for certain legacy McAfee ePO/DLP versions. Check with the Strac team for exact version compatibility.
7. Conclusion
Trellix (McAfee) Enterprise DLP delivers comprehensive data protection for modern enterprises—but too often, the sheer volume of alerts can tax your security resources. With Strac in the mix, you supercharge DLP with AI-driven triage, drastically reducing false positives and enabling your analysts to concentrate on what really matters: protecting sensitive data from genuine threats.