NVIDIA Megatron-LM: Checkpoint loading reaches remote code execution when a user loads a crafted checkpoint
Impact
Checkpoint loading reaches remote code execution when a user loads a crafted checkpoint - the highest-value path in this family, since checkpoints move between organisations routinely. In an AI datacenter this is the model-and-data supply chain problem: the code runs with whatever the training or inference job holds, which is usually a GPU, a service account, and mounted object storage credentials.
Who can reach it
Requires the job to load an attacker-influenced artifact - a checkpoint, .nemo file, config, tokenizer or dataset. Any pipeline that pulls from a public model hub, a customer bucket, or a tenant-supplied path is in scope.
What to do
Bump the package to the fixed version in bulletin 5769 and rebuild every training/inference image that embeds it. Cost: image rebuild and job restart; no host driver or firmware change. The durable control is refusing to deserialize untrusted checkpoints at all - prefer safetensors-style formats and treat pickle-bearing artifacts as executable code.
References
Related entries
- NVIDIA Megatron-LM: The inferencing path reaches remote code execution on crafted inputCVE-2026-24151 · NVIDIA Megatron-LMHigh
- NVIDIA Megatron-LM: A second checkpoint-loading remote code execution pathCVE-2026-24152 · NVIDIA Megatron-LMHigh
- NVIDIA Megatron-LM: A code-injection flaw in the tools component executes attacker-controlled code inside the trainingCVE-2025-23305 · NVIDIA Megatron-LMHigh
- NVIDIA Megatron-LM: megatron/training/arguments.py injects code from malicious inputCVE-2025-23306 · NVIDIA Megatron-LMHigh
- NVIDIA Megatron-LM: crafted input files execute attacker code in training and evaluation scriptsCVE-2025-23348 · NVIDIA Megatron-LMHigh
- NVIDIA Megatron-LM: A script in the repository injects code from crafted dataCVE-2025-23357 · NVIDIA Megatron-LMHigh
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.