GPU VulnDB

Database/AI/ML frameworks & serving

llama.cpp: a crafted GGUF file trips a reachable assertion and aborts the process loading it

CVE-2026-52131AI/ML frameworks & servingcurated

Impact

The GGUF reader hits an assertion it can be driven into by a malformed model file, terminating the process instead of rejecting the input. On a GPU node this is availability only - the record describes a reachable assertion, not memory corruption, and there is no claim of code execution or data disclosure. It matters where model files arrive from somewhere the operator does not fully control: a tenant-supplied model, a shared model cache, or a registry pull into a serving pod. An abort on a loaded model server frees the GPU but drops in-flight requests and, under a restart loop, can keep an expensive accelerator idle-cycling rather than serving.

Who can reach it

Anyone who can place or supply a GGUF file that the process later reads - a tenant uploading a model, a shared model volume, or an untrusted Hub artifact. No authentication to the server itself is implied by the record; the file is the input.

What to do

The record states only that builds b5693 and earlier are affected and names no fixed build - check the llama.cpp repository for the commit that guards this path before planning the change, and do not assume a version. Until then, treat model files as untrusted input: validate or convert GGUF artifacts in a sandboxed loader rather than in the serving process, and restrict who can write to shared model directories. Rolling a new build means restarting the inference server process; no node drain or reboot is involved.

References

Related entries

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This entry is curated: imported from vendor advisories with machine assistance, not yet individually verified. Confirm against your vendor's advisory before acting, and report anything wrong.