High · published November 22, 2025
⚠️ A seemingly innocent GGUF file can bring your machine learning application to its knees! 🥴 Think of it like a popular recipe book with a misprinted page — if you blindly follow it, you might end up with a kitchen disaster instead of a delicious meal! An attacker could craft a malicious GGUF file that, when loaded, leads to an application crash. This unexpected failure could disrupt crucial machine learning tasks, causing frustrating downtime. While it’s not an immediate catastrophe, it's definitely something you'd want to address swiftly to keep your projects running smoothly.
Think of it like a popular recipe book with a misprinted page — if you blindly follow it, you might end up with a kitchen disaster instead of a delicious meal! This vulnerability is due to a segmentation fault in the mlx::core::load_gguf() function, where an untrusted pointer from the gguflib library is dereferenced without proper validation. This results in application instability when parsing malicious GGUF files.
An attacker could craft a malicious GGUF file that, when loaded, leads to an application crash. This unexpected failure could disrupt crucial machine learning tasks, causing frustrating downtime. While it’s not an immediate catastrophe, it's definitely something you'd want to address swiftly to keep your projects running smoothly. Upgrade MLX to version 0.29.4 immediately to patch this issue. Additionally, implement input validation to ensure that GGUF files are properly checked before processing them. Regularly review your dependencies and stay updated on security patches. You've got this! Follow these steps, and you'll keep your MLX framework safe and sound! 🛡️
| Product | Versions | Fixed in |
|---|---|---|
| ml-explore/mlx | < 0.29.4 | 0.29.4 |