Threat database

GPT Academic version 3.83 is vulnerable to a Local File Read (LFI) vulnerability through its HotReload function. This function can download and extract tar.gz files from arxiv.org. Despite implementing protections against path traversal, the application overlooks the Tarslip triggered by symlinks. This oversight allows attackers to read arbitrary local files from the victim server.

In binary-husky/gpt_academic version <= 3.83, the plugin `CodeInterpreter` is vulnerable to code injection caused by prompt injection. The root cause is the execution of user-provided prompts that generate untrusted code without a sandbox, allowing the execution of parts of the LLM-generated code. This vulnerability can be exploited by an attacker to achieve remote code execution (RCE) on the application backend server, potentially gaining full control of the server.

A vulnerability in binary-husky/gpt_academic version 3.83 allows an attacker to cause a Denial of Service (DoS) by adding excessive characters to the end of a multipart boundary during file upload. This results in the server continuously processing each character and displaying warnings, rendering the application inaccessible. The issue occurs when the terminal shows a warning: 'multipart.multipart Consuming a byte '0x2d' in end state'.

A Cross-Site Request Forgery (CSRF) vulnerability in version 3.83 of binary-husky/gpt_academic allows an attacker to trick a user into uploading files without their consent, exploiting their session. This can lead to unauthorized file uploads and potential system compromise. The uploaded file can contain malicious scripts, leading to stored Cross-Site Scripting (XSS) attacks. Through stored XSS, an attacker can steal information about the victim and perform any action on their behalf.