What is AI-Native Cybersecurity?

Lucia Stanham - January 26, 2024

The application of artificial intelligence (AI) to cybersecurity is a game-changer for protecting modern enterprises and their digital assets. AI-native cybersecurity enables organizations to use the strengths of modern, cloud-native data platforms and cutting-edge AI to analyze vast datasets, identify patterns, and strengthen their security posture. Beyond enabling faster threat response, AI is helping enterprises predict and prevent potential cyber threats, allowing security teams to operate proactively and stay ahead of increasingly sophisticated attacks.

In this post, we’ll look at specific ways that AI is transforming cybersecurity. We’ll cover some key areas where AI-native capabilities are enhancing cybersecurity, such as threat detection, behavioral analysis, and endpoint protection. Then, we’ll highlight how platforms like CrowdStrike Falcon® are using AI to offer advanced cybersecurity solutions.

Let’s start by considering our first key area: threat detection.

The role of AI in threat detection

Threat detection is the process of identifying potential cybersecurity threats, such as malware, unauthorized access, or other types of malicious activity. As a part of your cybersecurity strategy, threat detection is the first step in mitigating threats. By recognizing threats early enough, an organization has sufficient lead time to prevent damage.

In AI-native cybersecurity, conducting real-time analysis at machine speed can significantly enhance threat detection. AI systems can process and analyze data at a speed and scale that would be impossible even for large teams of human analysts. These systems can  recognize subtle patterns and anomalies  that would be imperceptible to the human eye.

AI-native cybersecurity also provides predictive capabilities, using historical data to anticipate and prevent future attacks and adversary patterns. This enables a more proactive approach to threat detection.

Learn More

Learn how CrowdStrike’s Charlotte AI will democratize security and help every user — from novice to security expert — operate like a power user of the Falcon platform to speed detection, response, and help close the cybersecurity skills gap with three powerful use cases.Blog: Introducing Charlotte AI, CrowdStrike’s Generative AI Security Analyst

AI-powered indicators of attack

AI-powered behavioral analysis, which is enabled through indicators of attack (IOAs), has become pivotal to proactive defense strategies. While traditional security methods rely on recognizing known threats with signatures, IOAs focus on detecting the intentions or actions that signal active or in-progress attacks. As cyberattackers constantly adapt their methods to a shifting landscape, security teams can use IOAs to outpace attackers by making it harder for them to evade detection.

By leveraging AI-powered behavioral analysis, organizations can analyze hyperscale volumes of data to discern genuine threats from benign anomalies, detecting more advanced attacks with high levels of accuracy and reducing false positives. This can help prevent  alert fatigue and lightens the burden on security teams.

Finally, AI enables security defenses to adapt to evolving threats. Adversary tradecraft is  continually morphing and evolving, but AI-powered IOAs likewise learn and adapt. With AI-native cybersecurity, an enterprise’s defenses remain robust against ever-changing attack techniques.

Behavioral analysis and user and entity behavior analytics

User and entity behavior analytics (UEBA) leverages AI/machine learning (ML) to analyze and understand the behavior of users and entities within a network. By monitoring and analyzing activity, UEBA tools can identify actions that indicate a possible security threat. UEBA is particularly effective in detecting insider threats, compromised accounts, and other forms of malicious activity that might otherwise go unnoticed.

Core to UEBA’s function is user behavior profiling, in which AI algorithms analyze patterns of user activity to establish a baseline of normal behavior. With the baseline in place, UEBA tools can flag activities that deviate from the norm, signaling potential security events. In addition to monitoring user actions, UEBA performs entity behavior monitoring, tracking and analyzing the behavior of devices, applications, and network components. This holistic approach ensures that any unusual activity — whether from a user or a machine — is quickly and accurately identified.

Of course, the real power of UEBA in AI-native cybersecurity is its ability to perform contextual analysis. The AI systems underlying UEBA don’t just look at actions in isolation; they understand the context behind those actions, distinguishing between activities that could be in service of adversary objectives and benign atypical behavior

In fueling UEBA, AI-native cybersecurity offers a nuanced and sophisticated approach to security, moving beyond the traditional, rule-based systems of the past.

Automated response

When delivered as part of a cross-domain platform, AI-native security enables organizations to assess behavior across domains, further fueling an adaptive, proactive defense that can detect emerging tradecraft.

Central to this adaptive defense is automated response and remediation. AI brings automation to the endpoint level, instantly responding to threats and taking actions like isolating a device from the network or deleting malicious files. This automation is pivotal in containing threats before they spread or cause damage.

AI systems can also enable a self-improving security posture for organizations. As AI-native cybersecurity tools encounter new threats, they learn and evolve, continuously enhancing their ability to detect and respond to future threats and providing proactive recommendations to mitigate vulnerabilities across user environments. Despite the ever-changing landscape of cyber threats, AI-native cybersecurity remains adaptive and effective.

Learn More

AI is a cybersecurity game-changer given ML’s ability to detect behavior-based IOAs in real time. Leveraging cloud-native ML models trained on the rich telemetry of the CrowdStrike® Security Cloud, threat intelligence pointing to a hands-on-keyboard attack can be delivered to security teams to prevent real-time breaches from happening. Learn more!Blog: Using AI and ML to Combat Hands-on-Keyboard Cybersecurity Attacks

AI-native cybersecurity with CrowdStrike Falcon

Though we’ve covered specific areas where AI is transforming cybersecurity, we should also note that AI-native cybersecurity helps ensure smooth integration among all layers of the security stack. An integrated approach to cybersecurity creates a comprehensive posture that covers all aspects of an organization’s digital infrastructure.

The CrowdStrike Falcon platform represents the cutting edge of AI-native cybersecurity. AI enhances CrowdStrike Falcon® Identity Threat Detection to provide visibility into identity-based attacks and thwart lateral attack movement within networks. The Falcon platform also leverages AI-powered IOAs and AI-powered behavioral analysis for enhanced threat detection. CrowdStrike Falcon® Insight XDR brings AI-native capabilities to extended endpoint threat detection and response.

Tools like ExPRT.AI from CrowdStrike Falcon® Spotlight bring AI-native capabilities to vulnerability management, and CrowdStrike® Charlotte AI™ leverages the latest in generative AI to provide an intelligent security assistant to help users of all skill levels as they take on the complexities of DevSecOps.

For more information about how the CrowdStrike Falcon platform brings modern enterprises the best of AI-native cybersecurity, contact us today.


Lucia Stanham is a product marketing manager at CrowdStrike with a focus on endpoint protection (EDR/XDR) and AI in cybersecurity. She has been at CrowdStrike since June 2022.