Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The conventional approach to AI-powered security is to build an offensive agent to find weaknesses, build a defensive agent to catch threats, and run them in separate tracks. It's a clean division of labor that produces capable tools. However, the conventional approach also produces a permanent blind spot — the defense is never trained against the actual offense, and the connective tissue between the two is manual, slow, and fragile.

Modern data security depends on understanding sensitive data as it is created, accessed, and moved in real time directly on the endpoint. In addition to identifying predefined patterns such as credit card numbers or Social Security numbers, organizations must protect unstructured information including documents, chat logs, support tickets, AI prompts, medical records, and free-text fields.

CrowdStrike Counter Adversary Operations identified a financially motivated threat actor who works as a bug bounty hunter and who developed and distributed the JavaScript (JS)-based information stealer PhantomRaven via npm, a platform on which developers can access open-source packages to build applications and software.

Software supply chain attacks pose a critical enterprise threat. In the first half of 2026, these attacks increasingly used malicious software packages uploaded to public software registries, the CrowdStrike 2026 Threat Hunting Report found. Adversaries are poisoning open-source packages and exploiting the same dependencies that AI-assisted development tools and agentic applications pull onto enterprise endpoints every day.

The average adversary breakout time is now 29 minutes, with the fastest recorded at 27 seconds, according to the CrowdStrike 2026 Global Threat Report. AI is supercharging the adversary playbook, empowering many to move faster across multiple domains. Defenders must match that speed with AI-driven security operations that investigate and respond across every domain, in real time.

AI agents are evolving identity as we know it. They execute code, invoke tools, access applications and sensitive data, and take action on behalf of humans and systems. Increasingly, they operate autonomously and delegate work to other agents. They work at machine speed.

On August 31, 2026, CrowdStrike's Counter Adversary Operations team, in collaboration with international law enforcement and industry partners, executed a coordinated disruption of the Sality peer-to-peer (P2P) botnet, a criminal infrastructure that has operated with seeming impunity for more than two decades. The botnet enabled the operator to distribute malicious payloads to over 15,000 infected machines worldwide.

AI has rapidly evolved into a technology that takes action. AI agents can reason, access enterprise systems, and execute tasks autonomously at machine speed, often with the full permissions of the users they serve. As these agents proliferate across the enterprise, organizations need to understand where they operate, what they do, what they can access, and how to stop threats before they become breaches. This shift demands a new approach to AI security.

We are proud to announce that Frost & Sullivan has named CrowdStrike as the strongest overall leader in the Frost Radar: Cloud Workload Protection Platforms, 2026. CrowdStrike earned the highest scores in Innovation and Growth among 18 companies benchmarked from a field of more than 45 qualified participants. Today’s cloud attacks are designed to hide in plain sight.

Public benchmarks in AI provide important signals and allow for regression testing, directional validation of model updates, and public discussion of capabilities and limitations. But the more attention a benchmark receives, the stronger the incentive to optimize for it. Once a score becomes the goal, teams start benchmaxxing: optimizing for the benchmark rather than the capability it is meant to measure. This is a familiar problem in the AI space.