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2026 Cybersecurity Statistics and Threat Trends
The 2026 ExtraHop Global Threat Landscape Report
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AI Threat Landscape
AI Adoption and the Evolving Threat Landscape
AI is expanding the attack surface and reshaping risk priorities.
Every AI agent, generative application, and autonomous workflow added to the enterprise creates a new potential foothold for attackers.
55% of organizations cite AI agents and generative AI applications as their most significant cybersecurity risk.
AI-driven threats are behind a growing number of cybersecurity incidents.
When evaluating security incidents, data exposures, or "near-misses" where the root cause was an AI system over the last year, organizations reported experiencing the following:
| Incidence Rate | Threat Vector | Primary Root Cause |
|---|---|---|
Incidence Rate 40% | Threat Vector AI-Enhanced External Attack | Primary Root Cause AI-driven automation used for reconnaissance, phishing, and lateral movement |
Incidence Rate 38% | Threat Vector Compromised AI Identity & Session Theft | Primary Root Cause Unauthorized access to AI infrastructure via stolen tokens and API keys |
Incidence Rate 36% | Threat Vector Third-Party Vendor/Supply Chain Breach | Primary Root Cause Vulnerabilities introduced by integrated third-party AI or agents |
Incidence Rate 35% | Threat Vector Internal Shadow AI Exposure | Primary Root Cause Employees exposing proprietary data to unvetted public AI tools |
Incidence Rate 31% | Threat Vector Agentic/API Logic Failure | Primary Root Cause Autonomous agents (internal or external) executing unintended actions or hallucinating commands |
The velocity of AI-driven threats is rapidly outpacing cybersecurity defenses.
While adversaries operate at machine speed, security teams are still working at human pace, bogged down by manual workflows across the entire threat lifecycle.
- Threat detection required manual intervention 42% of the time.
- Alert triage required manual intervention 43% of the time.
- Investigation required manual intervention 49% of the time.
- Response required manual intervention 47% of the time.
SOC analysts are limited to spending just 44% of their time on proactive efforts like threat hunting and detection engineering, leaving the bulk of their hours dedicated to reactive triage and manual data gathering.
To address manual workloads, SOCs are investing in agentic AI, but it's proving to be a double-edged sword. AI-generated false positives delay security investigations nearly 30% of the time.
AI Threat Statistics
Methodology: Respondents: 1,800+ | Seniority: Director+ | Organization size: 1,000+ employees | Countries: UK | US | AU | SG | UAE | FR | DE
Threat Actor Activity and Enterprise Exposure
Which threat actors were most detected across enterprise networks?
- LockBit: 21%
- RansomHub: 20%
- Lazarus Group: 17%
- DarkSpectre: 16%
- Midnight Blizzard/APT29/Nobellium/Cozy Bear: 15%
- Scattered Spider: 14%
- ALPHV/Black Cat: 14%
- Black Basta: 14%
- Volt Typhoon: 13%
- Akira: 13%
Threat Tactics
Which threat actors were most detected across enterprise networks?
- AI agents and generative AI applications
- Public cloud (AWS, Google, Azure, etc.)
- Third-party services and integrations
- Identity management/identity infrastructure
- Private cloud
What are the top initial points of entry for attackers?
- Phishing and social engineering
- Software vulnerabilities
- Compromised credentials or brute-force attacks
- Third-party/supply chain compromise
- Software misconfigurations
What evasive techniques are threat actors using?
- Compromised credentials: Organizations experience an average of 3 security incidents or "near-misses" that involve attackers using compromised credentials.
- Encrypted evasion: Organizations experience an average of 2.8 security incidents or "near-misses" that involve attackers using encrypted evasion.
- Living-off-the-land: Organizations experience an average of 2.7 security incidents or "near-misses" that involve attackers using living-off-the-land techniques.
Ransomware
What does the ransomware landscape look like in 2026?
- Enterprises experienced 3.5 ransomware incidents in the last 12 months (on average).
- Organizations paid an average of $2.8 million in total ransomware payments in the last 12 months.
What are common challenges in ransomware detection?
- 49% of organizations didn’t detect ransomware until the data exfiltration stage or later (encryption or ransomware demand).
- Threat actors spend an average of almost 2.5 weeks in the network during a ransomware incident.
SOC Performance
It typically takes enterprises 2 weeks to respond to and contain a security alert from initial detection to resolution.
What delays a critical alert from being detected or investigated?
- 41% said attackers used encrypted channels to bypass detection
- 38% said attacker activity mirrored legitimate, authorized workflows and processes
- 34% said valid, high-privilege account permissions were used
- 30% said alert fatigue caused initial detection to be deprioritized
- 27% said undetermined baseline behavior enabled anomalous actions to go undetected
- 26% said they lacked logs to understand the specific protocol used during the attacks
Enterprises experience 30 hours of downtime per security incident on average.
