Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Sensitive information disclosure ranks on the OWASP Top 10 for LLM Applications, and for good reason. When AI-powered applications inadvertently expose private data like personally identifiable information (PII), financial records, health information, API keys, or proprietary business intelligence, the consequences cascade quickly: regulatory violations, competitive disadvantage, and shattered user trust.

The CrowdStrike Falcon platform delivered flawless 100% detection, 100% protection, and zero false positives in the 2025 MITRE ATT&CK Enterprise Evaluations, the industry's most demanding and comprehensive cross-domain security assessment to date. CrowdStrike's results demonstrate the precision and real-world effectiveness of the AI-native Falcon platform, which excelled in MITRE's expanded evaluation — now spanning endpoint, identity, and cloud security across hybrid environments.

CrowdStrike is introducing two powerful innovations in CrowdStrike Falcon Shield to stop identity-based attacks in the AI era: a centralized view of AI agents across platforms and the integration of first-party SaaS telemetry into CrowdStrike Falcon Next-Gen SIEM — the industry’s first native integration of SaaS security posture management (SSPM) and next-gen SIEM.

The rapid adoption of AI has introduced a new, semantic attack vector that many organizations are ill-prepared to defend against: prompt injection. While many security teams understand the threat of direct prompt injection attacks against AI agents developed by their organizations, another more subtle threat lurks in the shadows: indirect prompt injection attacks.

Throughout 2025, CrowdStrike has identified multiple intrusions targeting VMware vCenter environments at U.S.-based entities, in which newly identified China-nexus adversary WARP PANDA deployed BRICKSTORM malware. WARP PANDA exhibits a high level of technical sophistication, advanced operations security (OPSEC) skills, and extensive knowledge of cloud and virtual machine (VM) environments.