Attackers are moving faster, blending in better, and increasingly using AI to stay ahead of defenders.
The Crowdstrike 2026 Global Threat Report highlights a shift toward stealthy, identity-driven attacks that are harder to detect and quicker to execute.
“This is an AI arms race. Breakout time is the clearest signal of how intrusion has changed. Adversaries are moving from initial access to lateral movement in minutes,” said Adam Meyers, head of counter adversary operations at CrowdStrike in their press release.
He added,” AI is compressing the time between intent and execution while turning enterprise AI systems into targets. Security teams must operate faster than the adversary to win.”
Inside the Crowdstrike 2026 Global Threat Report Findings
The report highlights a fundamental shift in how modern attacks are executed, creating new challenges for security teams.
Rather than relying on traditional malware, adversaries are increasingly operating through legitimate systems and trusted access paths.
In 2025, 82% of detections were malware-free, underscoring how attackers are bypassing signature-based defenses by blending into normal activity.
Identity Abuse and Living-Off-the-Land Techniques
This evolution is closely tied to identity abuse. Instead of exploiting obvious vulnerabilities, attackers are using valid credentials, approved SaaS integrations, and legitimate identity workflows to move laterally across environments.
This living-off-the-land approach allows them to operate quietly within trusted systems, making detection more difficult.
Faster Breakout Times and Reduced Response Windows
At the same time, adversaries are moving faster than ever.
The average breakout time — the window between initial access and lateral movement — dropped to just 29 minutes, with some attacks occurring in under 30 seconds.
This compressed timeline leaves little opportunity for manual response and requires organizations to rely on automated detection and rapid containment capabilities.
AI-Enabled Attacks Are Scaling Threats
AI is further accelerating this trend. CrowdStrike observed an 89% increase in activity from AI-enabled adversaries, who are using these tools to scale social engineering campaigns, automate reconnaissance, and improve targeting precision.
Generative AI, in particular, is being used to craft more convincing phishing lures and streamline attack workflows, lowering the barrier to entry for sophisticated attacks.
AI Systems Become a New Attack Surface
In addition to using AI as a force multiplier, threat actors are also targeting AI systems themselves.
Techniques such as prompt injection allow attackers to manipulate GenAI tools into generating malicious commands, enabling credential theft or data exfiltration.
As organizations integrate AI into development pipelines and business operations, these systems are becoming a new and expanding attack surface.
Supply chain compromise remains another critical vector in this evolving threat landscape.
Attackers are increasingly targeting upstream providers, development ecosystems, and shared dependencies to gain access to multiple downstream organizations at once.
When combined with a 42% increase in zero-day exploitation before public disclosure, these tactics make attacks more scalable, harder to detect, and more difficult to mitigate using traditional approaches.
Together, these trends illustrate a broader shift toward faster, stealthier, and more adaptive adversaries — forcing organizations to rethink how they detect, respond to, and defend against modern threats.
How to Reduce Exposure to Emerging Threats
To keep pace with these evolving threats, organizations should adopt a more proactive and layered security approach.
- Strengthen identity security by enforcing phishing-resistant MFA, least privilege, and continuous monitoring for credential misuse and abnormal access patterns.
- Monitor endpoints, cloud, and SaaS environments for anomalous behavior using correlated telemetry.
- Reduce exposure to vulnerabilities and unknown assets by prioritizing rapid patching and implementing continuous attack surface management.
- Restrict lateral movement and execution risk through network segmentation, zero trust principles, and isolated environments for AI and untrusted workloads.
- Secure AI systems and workflows by validating inputs, monitoring for prompt injection, and enforcing strict access controls and governance.
- Harden systems and data by enforcing privileged access controls, protecting sensitive data with encryption or DLP, and securing developer and edge environments.
- Test incident response plans, use attack simulation tools and conduct red team exercises.
These steps help organizations reduce exposure and build resilience for emerging threats.
AI and the New Cyber Threat Landscape
The CrowdStrike findings point to an ongoing shift in cybersecurity, where attackers are adapting their techniques by using AI and trusted access to evade traditional defenses.
As enterprise environments become more complex and interconnected, distinguishing between normal and malicious activity is becoming more challenging.
To address these challenges, organizations are turning to zero trust solutions that prioritize continuous verification and limit implicit trust across environments.