CrowdStrike Signal – A New Level of Threat Detection Based on AI

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CrowdStrike announced the general availability of CrowdStrike Signal – the next generation of AI engines for detecting threats that remain unnoticed by other solutions. Signal uses self-learning models that study what behavior is normal for each host, user, and system, detecting even the slightest deviations that may indicate an attack at an early stage.

Unlike traditional tools or systems with fixed rules, Signal does not wait for the threat to manifest – it recognizes suspicious activity immediately, even if it appears harmless. The system adapts to changes in the environment, detecting and linking weak signals to form highly accurate prioritized lead alerts.

CrowdStrike Signal – A New Level of Threat Detection Based on AI - image 1

KEY FEATURES OF CROWDSTRIKE SIGNAL

1. Self-learning AI

Constantly analyzes the behavior of each user, host, and process, adapting to changes without manual tuning.

2. Real-time hidden threat detection

Detects low-level activity that often goes unnoticed, including the use of system tools for reconnaissance.

3. Reduction of false alerts

Consolidates massive amounts of data into a narrow set of prioritized lead events, accelerating investigation and response.

“Signal is a breakthrough designed to detect those subtle signs of attacks that usually go unnoticed,” said Eliya Zaitsev, CrowdStrike’s Chief Technology Officer.

The CrowdStrike Falcon platform, built in the cloud and powered by artificial intelligence, combines real-time telemetry, threat intelligence, and adversary action analytics. Falcon provides accurate attack detection, automatic protection, proactive threat hunting, and prioritized visibility of vulnerabilities. Thanks to its lightweight agent and cloud-built architecture, the platform is rapidly deployable, scales without performance loss, and reduces the complexity of cybersecurity.

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