A vulnerability in the binary-husky/gpt_academic repository, as of commit git 3890467, allows an attacker to crash the server by uploading a specially crafted zip bomb. The server decompresses the uploaded file and attempts to load it into memory, which can lead to an out-of-memory crash. This issue arises due to improper input validation when handling compressed file uploads.

A Denial of Service (DoS) vulnerability exists in the file upload feature of binary-husky/gpt_academic version 3.83. The vulnerability is due to improper handling of form-data with a large filename in the file upload request. An attacker can exploit this vulnerability by sending a payload with an excessively large filename, causing the server to become overwhelmed and unavailable for legitimate users.

A vulnerability in binary-husky/gpt_academic version 310122f allows for a Regular Expression Denial of Service (ReDoS) attack. The application uses a regular expression to parse user input, which can take polynomial time to match certain crafted inputs. This allows an attacker to send a small malicious payload to the server, causing it to become unresponsive and unable to handle any requests from other users.