CrowdStrike Signal Delivers the Next Evolution of AI-Powered Threat Detection

CrowdStrike has announced the general availability of CrowdStrike Signal, a new class of Artificial Intelligence (AI)-powered detection engines that surface the undetectable threats others miss—before they escalate. Signal uses self-learning models for every host to understand what is normal in that environment across time, systems, and users. It pinpoints subtle, early-stage threat activity and connects related behaviours before traditional tools act.

By identifying weak signals that deviate from the norm and building high-confidence, prioritised leads, CrowStrike Signal accelerates the Falcon® platform’s AI advantage and empowers security teams to investigate, hunt, and stop threats earlier in the kill chain.

Modern attacks often begin with low-signal activity that appears benign in isolation. Traditional rule-based systems ignore these behaviours because they lack the context to tell what is suspicious and what is just noise. Even newer AI approaches apply scoring only after a detection has occurred.

Signal learns what’s normal across the environment and continuously updates its understanding of standard activity as conditions change—identifying what deviates and linking early-stage behaviours with downstream activity. By analysing behaviour earlier in the threat lifecycle and correlating subtle activity across time, CrowdStrike Signal turns fragmented signals into a small number of prioritised, AI-generated leads that expose threats buried in the noise and jumpstart response. Born on the endpoint, CrowdStrike Signal lays the foundation for next-generation detection across identity, cloud, and third-party data.

“CrowdStrike pioneered AI-native cybersecurity, and continues to deliver the innovation driving the industry forward. CrowdStrike Signal is our latest breakthrough, built to detect how modern adversaries actually operate,” said Elia Zaitsev, Chief Technology Officer at CrowdStrike. “Today’s attackers spread subtle signals over time to stay under the radar. Signal is designed to catch what others overlook, connecting the dots across systems and time to paint the full picture.”

CrowdStrike Signal Through the Noise

Behind CrowdStrike Signal is a new family of statistical time series models that analyze billions of daily events within each customer’s environment. By linking signals across time and systems, Signal filters out repetitive activity and surfaces what is truly unusual. This correlation builds high-confidence patterns that reveal stealthy attacker behavior before others can, giving defenders a clear starting point to act.

• Self-learning AI to Understand the Customer Environment: Signal continuously models behaviour for each user, host, and process, adapting over time to surface meaningful deviations. Unlike static rules or pre-trained models, it delivers early-stage detection without manual configuration or constant adjustment.
• Real-time Detection of Stealthy Tradecraft Others Miss:Signal links subtle behaviours often used by attackers – but also commonly seen on benign hosts—such as the use of living-off-the-land tools for reconnaissance or applications running from temporary directories. This low-signal activity may appear benign in isolation, but analysed earlier, over time and context, it reveals attacker activity that would otherwise go unnoticed.
• High-confidence Leads Reduce Alert Volume, Accelerate Response:Signal condenses a vast number of behaviours and detections into a small set of high-fidelity leads. It surfaces early indicators of compromise, reduces false positives, and groups related activity into a single starting point to eliminate manual triage and speed investigation, hunting, and response.

CrowdStrike Signal is now generally available. To learn more, read the CrowdStrike blog.