Over 1,100 Exposed LLM Servers: A Security Vulnerability Deep Dive

Researchers discovered over 1,100 publicly exposed LLM servers running the Ollama framework, with approximately 20% actively hosting models vulnerable to unauthorized access. Using Shodan and a Python-based tool, the study revealed a critical lack of security baselines in LLM deployments, providing a foundation for future LLM threat surface monitoring. Vulnerabilities included unauthorized API access, model extraction attacks, jailbreaking and content abuse, resource hijacking, and backdoor injection. The researchers recommend several security mitigations, including enforcing authentication and access control, network segmentation and firewalls, rate limiting and abuse detection, disabling default ports, and continuous monitoring to secure LLM infrastructure.