Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

As AI agents become increasingly prevalent across business environments, their security is a pressing concern. Among the insidious threats facing AI agents is tool poisoning, a type of attack that exploits the way AI agents interpret and use tool descriptions to guide their reasoning. In this blog, we explain how AI tool poisoning works, the different forms it can take, and how organizations can strengthen their defenses against this type of attack.

I’m excited to announce CrowdStrike’s agreement to acquire SGNL, a leader in identity-first security. This acquisition will extend CrowdStrike Falcon Next-Gen Identity Security to deliver continuous, context-aware authorization for human, non-human, and AI agent identities across SaaS and hyperscaler cloud environments. As risk conditions and threats change, access to applications, data, and AI agents should change with them.

At Fal.Con 2025, CrowdStrike introduced Threat AI, an agentic threat intelligence system of autonomous agents that reason across data, hunt for threats, and take action. As part of our vision for the agentic SOC, these AI-powered agents automate complex intelligence workflows so defenders can keep up with AI-powered adversaries while staying in control of every decision.

Today’s security teams need AI models that can reason over massive telemetry and support autonomous actions. At CrowdStrike, we're working closely with NVIDIA to operationalize NVIDIA Nemotron open models1, building on our existing integration of Nemotron on Amazon Bedrock within the CrowdStrike Falcon platform. This collaboration enables us to rigorously test and adapt large language models (LLMs) for security-specific workloads while maintaining production-grade performance and security.

As IT environments grow more complex and adversaries move faster, security and IT teams need a reliable way to enforce configurations, maintain application health, and resolve issues at scale without writing or maintaining custom scripts. CrowdStrike Falcon for IT already gives operators powerful tools to query endpoints, run remediation, and enforce baseline configurations.

Large language models (LLMs) have revolutionized artificial intelligence and are rapidly transforming the cybersecurity landscape. As these powerful models become commonly used among both attackers and defenders, developing specialized cybersecurity LLMs has become a strategic imperative. The CrowdStrike 2025 Global Threat Report highlights a concerning trend: Threat actors are increasingly enhancing social engineering and computer network operations campaigns with LLM capabilities.

Security teams are at a critical inflection point. AI-enabled adversaries now operate at machine speed, automating phases of the kill chain and scaling attacks faster than human-only workflows can respond. Yet most SOCs still depend on manual triage and investigation processes that cannot keep pace.

Organizations are under pressure to protect more devices, users, and distributed workloads than ever — while adversaries are moving faster, smarter, and across more domains. Many businesses still depend on complex solutions that create gaps between tools and strain security teams.

Artificial intelligence is transforming how organizations operate, innovate, and compete. From employees using GenAI tools to boost productivity to engineering teams building sophisticated AI agents and applications, AI has become central to modern business operations. AI now operates across every part of the enterprise, spanning endpoints, applications, identities, cloud services, data, and SaaS platforms.

Today’s adversaries operate at machine speed. According to the CrowdStrike 2025 Global Threat Report, the average eCrime breakout time — from initial compromise to lateral movement — has dropped to just 48 minutes, down from 62 minutes in the previous year. Traditional vulnerability management can’t keep up.