CVE-2026-9856
HighCVSS 7.1Exploitation Probability (EPSS)
Low risk22th percentile - higher than 22% of all known CVEs
Summary
Hugging Face Transformers up to version 5.8.0.dev0 has an arbitrary file write vulnerability via path traversal in save_pretrained(). Keys from chat_template are used as filenames without validation.
Risk Assessment
An attacker can publish a malicious repository that, when downloaded and saved by a victim, overwrites arbitrary files on the victim's system.
Recommendation
Upgrade the transformers library to a patched version or restrict trust in downloaded tokenizers.
Other vulnerabilities in Hugging Face Transformers
See all- CVE-2026-80047High
A vulnerability in Hugging Face Transformers (versions 4.57.0 to 5.16.1) allows remote Python files to be written to local disk without user consent when using GenerativePreTrainedModel.load_custom_generate(). The function fetches and caches a remote module file before performing the required trust_remote_code consent check, inverting the security model enforced by other code-loading paths. As a result, attacker-controlled Python code from custom_generate/generate.py is copied into the user's ~/.cache/huggingface/modules directory even if the user declines the trust prompt.
- CVE-2026-75104Medium
Hugging Face Transformers fails to validate shard filenames in checkpoint index files, allowing attackers to read arbitrary files outside the model directory. Malicious index files with parent-directory references or absolute paths can lead to file disclosure and filesystem reconnaissance.
- CVE-2025-6051Medium
A ReDoS vulnerability was discovered in the Hugging Face Transformers library in the normalize_numbers() method of the EnglishNormalizer class. It affects versions up to 4.52.4 and is fixed in 4.53.0. Crafted input with long digit sequences can cause excessive CPU consumption.
Original NVD description (English source)
A vulnerability in huggingface/transformers versions <=5.8.0.dev0 allows an attacker to perform arbitrary file writes via path traversal. The issue resides in the `save_pretrained()` methods of `PreTrainedTokenizerBase` and `ProcessorMixin`, where keys from the `chat_template` dictionary are used directly as filenames without proper validation. An attacker can exploit this by publishing a malicious Hugging Face Hub repository with a crafted `tokenizer_config.json` file. When a victim downloads and saves the tokenizer or processor, the attacker-controlled keys can escape the intended save directory, enabling arbitrary file writes with attacker-controlled content. This vulnerability affects multiple processors inheriting from `ProcessorMixin`, including Idefics, Florence, Gemma, Phi, and Qwen-VL.
Vulnerability data from NVD (NIST) · CISA KEV · EPSS