Rocketknight1

**Name of the Vulnerable Software and Affected Versions** huggingface/transformers version v4.48.3 **Description** A vulnerability in the `preprocess string()` function of the `transformers.testing utils` module 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, effectively resulting in a Denial of Service (DoS) scenario. **Recommendations** As a temporary workaround, consider disabling the `preprocess string()` function until a patch is available. Restrict access to the `transformers.testing utils` module to minimize the risk of exploitation. Avoid using the `preprocess string()` function in the affected API endpoint until the issue is resolved. At the moment, there is no information about a newer version that contains a fix for this vulnerability.

**Name of the Vulnerable Software and Affected Versions** huggingface/transformers library version v4.48.1 **Description** 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 (DoS) scenario. **Recommendations** As a temporary workaround, consider disabling the `SubWordJapaneseTokenizer` class until a patch is available. Restrict access to the `tokenization gpt neox japanese.py` file to minimize the risk of exploitation. Avoid using the `tokenization gpt neox japanese.py` file in the affected API endpoint until the issue is resolved. At the moment, there is no information about a newer version that contains a fix for this vulnerability.

**Name of the Vulnerable Software and Affected Versions** huggingface/transformers (affected versions not specified) **Description** The issue allows for 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 enables remote code execution (RCE) by deceiving victims into loading a seemingly harmless checkpoint during a normal training process, thereby enabling attackers to execute arbitrary code on the targeted machine. **Recommendations** At the moment, there is no information about a newer version that contains a fix for this vulnerability.