Essential Data Sources for Detection Beyond the Endpoint

2026-05-01 · Source: Unit 42 · Field: Technology & Digital — Cybersecurity & Data Privacy, Cloud Computing & IT Infrastructure, Artificial Intelligence & Machine Learning · Depth: Intermediate, medium

Summary

The 2026 Unit 42 Global Incident Response Report reveals that threat actors are now moving 4x faster to exfiltration than in 2025, exploiting blind spots from over-reliance on endpoint data. The proliferation of cloud services, microservices, and remote users has expanded the attack surface beyond single-tool monitoring. In 75% of incidents, critical evidence was in logs but inaccessible. Endpoint-only views fail in scenarios like cloud-to-endpoint pivots, covert C2 and identity theft, and rogue assets. Unit 42 advocates for Security Operations Centers (SOCs) to adopt a "single-pane-of-glass" strategy, powered by an AI-driven platform like Cortex XSIAM. This approach consolidates all security logs into a single repository and processes all alerts in a centralized workbench, integrating data from 10 IT zones. This enables machine learning for alert stitching, incident scoring, and user/entity behavior analytics, enhancing threat detection and reducing alert fatigue.

Key takeaway

For Security Operations Center (SOC) teams aiming to counter rapidly accelerating threats, relying solely on endpoint detection is no longer sufficient. You must evolve your defense strategy to ingest and correlate telemetry from all IT zones, including cloud, IAM, and IoT. Implement an AI-driven, single-pane-of-glass platform to unify security logs and centralize alert processing, enabling machine learning to stitch events and prioritize incidents. This approach will provide the holistic visibility needed to proactively stop sophisticated attacks and reduce analyst fatigue.

Key insights

Over-reliance on endpoint security creates critical blind spots, necessitating holistic telemetry correlation across all IT zones.

Principles

• All security logs must reside in a single repository.
• All security alerts require processing in a centralized workbench.

Method

Implement an AI-driven SOC platform to consolidate diverse security data, automate detection, investigation, and response, and leverage ML for alert stitching and incident scoring.

In practice

• Integrate cloud security logs, CASB alerts, and EDR telemetry.
• Monitor network activity for shadow IT and unmanaged devices.
• Evaluate current visibility through a formal security assessment.

Topics

• Threat Detection
• Incident Response
• Cloud Security
• Identity and Access Management
• Security Operations Center
• AI-driven Security

Best for: CTO, VP of Engineering/Data, Executive, AI Security Engineer, Security Engineer, IT Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Unit 42.