CVE-2026-22778

This vulnerability is rated Critical rather than Important because it allows unauthenticated remote code execution without requiring user interaction, ultimately leading to full compromise of the affected system. An attacker can provide a malicious video URL to a vulnerable vLLM inference endpoint, which causes the service to automatically retrieve and process attacker-controlled media content. During decoding, a heap overflow is triggered in the underlying video processing stack, enabling corruption of heap memory and potential overwriting of control structures to execute arbitrary commands on the host. In addition, an information disclosure condition can leak memory addresses, significantly weakening ASLR protections and making exploitation more reliable when combined with the heap overflow. Successful exploitation compromises the confidentiality, integrity, and availability of the system and can impact deployments such as Red Hat AI Inference Server, Red Hat Enterprise Linux AI, and Red Hat OpenShift AI, thereby meeting Red Hat’s criteria for Critical severity rather than Important impact.

The vLLM vulnerability depends on CVE-2025-9951, as processing attacker-controlled media can trigger the JPEG2000 decoder heap overflow, which can then be exploited within the vLLM video handling pipeline to cause memory corruption and potentially achieve remote code execution.