CVE-2026-0599

A vulnerability in huggingface/text-generation-inference version 3.3.6 allows unauthenticated remote attackers to exploit unbounded external image fetching during input validation in VLM mode. The issue arises when the router scans inputs for Markdown image links and performs a blocking HTTP GET request, reading the entire response body into memory and cloning it before decoding. This behavior can lead to resource exhaustion, including network bandwidth saturation, memory inflation, and CPU overutilization. The vulnerability is triggered even if the request is later rejected for exceeding token limits. The default deployment configuration, which lacks memory usage limits and authentication, exacerbates the impact, potentially crashing the host machine. The issue is resolved in version 3.3.7.

An attacker identifies a publicly accessible TGI endpoint running in VLM mode — discoverable via Shodan or by probing common ports (8080, 8000) with the /info endpoint. They craft a POST to /generate containing a prompt with a Markdown image reference: `What do you see? `. The TGI router parses the Markdown, initiates a blocking HTTP GET to the attacker's server, and streams the full 10GB response into memory before any token-limit validation occurs. The attacker runs this concurrently from multiple IPs or even a single client with multiple threads. Within seconds to minutes (depending on bandwidth), the TGI process exhausts available RAM, triggering OOM kills and crashing the inference service — with no authentication required and no prior knowledge of the model or API needed.