GPT Academy version 3.83 in the binary-husky/gpt_academic repository is vulnerable to Cross-Site WebSocket Hijacking (CSWSH). This vulnerability allows an attacker to hijack an existing WebSocket connection between the victim's browser and the server, enabling unauthorized actions such as deleting conversation history without the victim's consent. The issue arises due to insufficient WebSocket authentication and lack of origin validation.
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.
GPT Academic version 3.83 is vulnerable to a Server-Side Request Forgery (SSRF) vulnerability through its HotReload plugin function, which calls the crazy_utils.get_files_from_everything() API without proper sanitization. This allows attackers to exploit the vulnerability to abuse the victim GPT Academic's Gradio Web server's credentials to access unauthorized web resources.
In version 3.83 of binary-husky/gpt_academic, a Server-Side Request Forgery (SSRF) vulnerability exists in the Markdown_Translate.get_files_from_everything() API. This vulnerability is exploited through the HotReload(Markdown翻译中) plugin function, which allows downloading arbitrary web hosts by only checking if the link starts with 'http'. Attackers can exploit this vulnerability to abuse the victim GPT Academic's Gradio Web server's credentials to access unauthorized web resources.
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 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.
An open redirect vulnerability exists in binary-husky/gpt_academic version 3.83. The vulnerability occurs when a user is redirected to a URL specified by user-controlled input in the 'file' parameter without proper validation or sanitization. This can be exploited by attackers to conduct phishing attacks, distribute malware, and steal user credentials.
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 path traversal vulnerability exists in binary-husky/gpt_academic version 3.83. The vulnerability is due to improper handling of the file parameter, which is open to path traversal through URL encoding. This allows attackers to view any file on the host system, including sensitive files such as critical application files, SSH keys, API keys, and configuration values.
A stored cross-site scripting (XSS) vulnerability exists in binary-husky/gpt_academic version 3.83. The vulnerability occurs at the /file endpoint, which renders HTML files. Malicious HTML files containing XSS payloads can be uploaded and stored in the backend, leading to the execution of the payload in the victim's browser when the file is accessed. This can result in the theft of session cookies or other sensitive information.