Advisories for Pypi/Transformers package

A Regular Expression Denial of Service (ReDoS) vulnerability exists in the Hugging Face Transformers library, specifically in the convert_tf_weight_name_to_pt_weight_name() function. This function, responsible for converting TensorFlow weight names to PyTorch format, uses a regex pattern /[^/]___([^/])/ that can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. The vulnerability affects versions up to 4.51.3 and is fixed in version 4.53.0. This issue can lead …

A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically within the DonutProcessor class's token2json() method. This vulnerability affects versions 4.51.3 and earlier, and is fixed in version 4.52.1. The issue arises from the regex pattern <s_(.*?)> which can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. This vulnerability can lead to service disruption, resource exhaustion, …

A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the get_configuration_file() function within the transformers.configuration_utils module. The affected version is 4.49.0, and the issue is resolved in version 4.51.0. The vulnerability arises from the use of a regular expression pattern config.(.*).json that can be exploited to cause excessive CPU consumption through crafted input strings, leading to catastrophic backtracking. This can result …

Hugging Face Transformers versions up to 4.49.0 are affected by an improper input validation vulnerability in the image_utils.py file. The vulnerability arises from insecure URL validation using the startswith() method, which can be bypassed through URL username injection. This allows attackers to craft URLs that appear to be from YouTube but resolve to malicious domains, potentially leading to phishing attacks, malware distribution, or data exfiltration. The issue is fixed in …

A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the huggingface/transformers repository, specifically in version 4.49.0. The vulnerability is due to inefficient regular expression complexity in the SETTING_RE variable within the transformers/commands/chat.py file. The regex contains repetition groups and non-optimized quantifiers, leading to exponential backtracking when processing 'almost matching' payloads. This can degrade application performance and potentially result in a denial-of-service (DoS) when handling specially crafted input strings. …

A Regular Expression Denial of Service (ReDoS) vulnerability was discovered in the Hugging Face Transformers library, specifically in the get_imports() function within dynamic_module_utils.py. This vulnerability affects versions 4.49.0 and is fixed in version 4.51.0. The issue arises from a regular expression pattern \stry\s:.?except.?: used to filter out try/except blocks from Python code, which can be exploited to cause excessive CPU consumption through crafted input strings due to catastrophic backtracking. This …

A vulnerability in the preprocess_string() function of the transformers.testing_utils module in huggingface/transformers version v4.48.3 allows for a Regular Expression Denial of Service (ReDoS) attack. The regular expression used to process code blocks in docstrings contains nested quantifiers, leading to exponential backtracking when processing input with a large number of newline characters. An attacker can exploit this by providing a specially crafted payload, causing high CPU usage and potential application downtime, …

A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file tokenization_gpt_neox_japanese.py of the GPT-NeoX-Japanese model. The vulnerability occurs in the SubWordJapaneseTokenizer class, where regular expressions process specially crafted inputs. The issue stems from a regex exhibiting exponential complexity under certain conditions, leading to excessive backtracking. This can result in high CPU usage and potential application downtime, effectively creating a Denial of Service …

A Regular Expression Denial of Service (ReDoS) vulnerability was identified in the huggingface/transformers library, specifically in the file tokenization_nougat_fast.py. The vulnerability occurs in the post_process_single() function, where a regular expression processes specially crafted input. The issue stems from the regex exhibiting exponential time complexity under certain conditions, leading to excessive backtracking. This can result in significantly high CPU usage and potential application downtime, effectively creating a Denial of Service (DoS) …

Hugging Face Transformers MobileViTV2 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of configuration files. The issue results from the lack of proper validation of …

Hugging Face Transformers Trax Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of model files. The issue results from the lack of proper validation …

Hugging Face Transformers MaskFormer Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the parsing of model files. The issue results from the lack of proper validation …

The huggingface/transformers library is vulnerable to arbitrary code execution through deserialization of untrusted data within the load_repo_checkpoint() function of the TFPreTrainedModel() class. Attackers can execute arbitrary code and commands by crafting a malicious serialized payload, exploiting the use of pickle.load() on data from potentially untrusted sources. This vulnerability allows for remote code execution (RCE) by deceiving victims into loading a seemingly harmless checkpoint during a normal training process, thereby enabling …

Deserialization of Untrusted Data in GitHub repository huggingface/transformers prior to 4.36.

Deserialization of Untrusted Data in GitHub repository huggingface/transformers prior to 4.36.0.

Insecure Temporary File in GitHub repository huggingface/transformers 4.29.2 and prior. A fix is available at commit 80ca92470938bbcc348e2d9cf4734c7c25cb1c43 and has been released as part of version 4.30.0.