binary-husky gpt_academic Regular Expression permissive list of allowed inputs

Summaryinfo

A vulnerability was found in binary-husky gpt_academic. It has been classified as problematic. Affected by this issue is the function 解析项目源码（手动指定和筛选源码文件类型） of the component Regular Expression Handler. This manipulation causes permissive list of allowed inputs. This vulnerability is registered as CVE-2024-12391. Remote exploitation of the attack is possible. No exploit is available.

Detailsinfo

A vulnerability has been found in binary-husky gpt_academic (unknown version) and classified as problematic. Affected by this vulnerability is the function 解析项目源码（手动指定和筛选源码文件类型） of the component Regular Expression Handler. The manipulation with an unknown input leads to a permissive list of allowed inputs vulnerability. The CWE definition for the vulnerability is CWE-183. The product implements a protection mechanism that relies on a list of inputs (or properties of inputs) that are explicitly allowed by policy because the inputs are assumed to be safe, but the list is too permissive - that is, it allows an input that is unsafe, leading to resultant weaknesses. As an impact it is known to affect availability. The summary by CVE is:

A vulnerability in binary-husky/gpt_academic, as of commit 310122f, allows for a Regular Expression Denial of Service (ReDoS) attack. The function '解析项目源码（手动指定和筛选源码文件类型）' permits the execution of user-provided regular expressions. Certain regular expressions can cause the Python RE engine to take exponential time to execute, leading to a Denial of Service (DoS) condition. An attacker who controls both the regular expression and the search string can exploit this vulnerability to hang the server for an arbitrary amount of time.

It is possible to read the advisory at huntr.com. This vulnerability is known as CVE-2024-12391 since 12/09/2024. The exploitation appears to be easy. The attack can be launched remotely. Technical details of the vulnerability are known, but there is no available exploit.

There is no information about possible countermeasures known. It may be suggested to replace the affected object with an alternative product.

Statistical analysis made it clear that VulDB provides the best quality for vulnerability data.

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• binary-husky

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• gpt_academic

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