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AI Infrastructure Vulnerabilities Targeted in 2026 Security Study

AI Infrastructure Vulnerabilities Targeted in 2026 Security Study

First seen 19 Oct 2026, 11:18 UTC • •
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ThreatCluster AI
ThreatCluster •October 19, 2026 at 12:49 UTC
  • •AI infrastructure vulnerabilities are increasingly targeted, not the AI models.
  • •1,467 exposed MCP servers found, some with unauthenticated access to sensitive data.
  • •Over 70% of sought-after exploits target vulnerabilities older than two years.

The State of AI Security study reveals that in the first half of 2026, attacks focused on AI infrastructure rather than the AI models themselves. Key vulnerabilities include unauthenticated access, unpatched software, and weak secret management, with 43,175 AI-related service instances identified across 25 industries. Notably, 1,467 exposed MCP servers were found, some allowing unauthenticated access to sensitive data. The report indicates that 85% of participants in the Pwn2Own competition utilized LLMs for security research, resulting in 47 zero-day exploits. Furthermore, over 70% of exploits sought after are targeting vulnerabilities older than two years. The findings suggest that AI is accelerating existing security issues rather than creating new ones, making traditional vulnerabilities harder to detect and contain.

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Timeline

2026-10-15
Snyk introduces Evo Agentic AppSec
Snyk announces a new application security program to address vulnerabilities introduced by AI-driven development, highlighting the imbalance in vulnerability management.
Snyk
2026-10-19
State of AI Security study published
The study reveals that AI infrastructure vulnerabilities are the primary focus for attackers in 2026, highlighting significant risks from exposed MCP servers.
B2B-Cyber-Security.De
2026-10-19
TrendAI Security report released
TrendAI's report confirms that AI is amplifying traditional security failures, making them harder to detect and contain.
TrendAI

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Common questions

What types of vulnerabilities are most common?
Common vulnerabilities include unauthenticated access, unpatched software, and weak secret management.
How many AI-related service instances were identified?
The study identified 43,175 AI-related service instances across 25 industries.
What is the significance of the Pwn2Own competition results?
The competition revealed that 85% of participants used LLMs for security research, leading to 47 zero-day exploits.