Tag
#vLLM
Uncontrolled Resource Consumption in vLLM: Understanding and Mitigating CVE-2026-116177
This educational analysis delves into CVE-2026-116177, an uncontrolled resource consumption vulnerability in vLLM, a Python package for efficient large language model inference. The vulnerability allows unauthenticated attackers to exhaust memory by submitting a pathological decompression-bomb image, potentially leading to denial-of-service (DoS) attacks. We will explore the root cause, attack surface, exploitation mechanics, real-world impact, and defensive strategies to mitigate this threat.
CVE-2026-116180: Critical Denial of Service Vulnerability in vLLM
A critical denial of service (DoS) vulnerability, CVE-2026-116180, has been discovered in vLLM, a popular AI model serving platform. The vulnerability affects versions from 0.8.5 to before 0.31.0 and allows an attacker to crash the EngineCore, impacting co-tenant requests. The CVSS score is 7.7, indicating a high severity. Immediate patching is recommended.