Security Vulnerabilities
- CVEs Published In March 2025
An unhandled exception in the danny-avila/librechat repository, version git 600d217, can cause the server to crash, leading to a full denial of service. This issue occurs when certain API endpoints receive malformed input, resulting in an uncaught exception. Although a valid JWT is required to exploit this vulnerability, LibreChat allows open registration, enabling unauthenticated attackers to create an account and perform the attack. The issue is fixed in version 0.7.6.
In lunary-ai/lunary before version 1.6.3, an improper access control vulnerability exists where a user can access prompt data of another user. This issue affects version 1.6.2 and the main branch. The vulnerability allows unauthorized users to view sensitive prompt data by accessing specific URLs, leading to potential exposure of critical information.
In lunary-ai/lunary before version 1.6.3, the application allows the creation of evaluators without enforcing a unique constraint on the combination of projectId and slug. This allows an attacker to overwrite existing data by submitting a POST request with the same slug as an existing evaluator. The lack of database constraints or application-layer validation to prevent duplicates exposes the application to data integrity issues. This vulnerability can result in corrupted data and potentially malicious actions, impairing the system's functionality.
A path traversal vulnerability exists in binary-husky/gpt_academic at commit 679352d, which allows an attacker to bypass the blocked_paths protection and read the config.py file containing sensitive information such as the OpenAI API key. This vulnerability is exploitable on Windows operating systems by accessing a specific URL that includes the absolute path of the project.
A pickle deserialization vulnerability exists in the Latex English error correction plug-in function of binary-husky/gpt_academic versions up to and including 3.83. This vulnerability allows attackers to achieve remote command execution by deserializing untrusted data. The issue arises from the inclusion of numpy in the deserialization whitelist, which can be exploited by constructing a malicious compressed package containing a merge_result.pkl file and a merge_proofread_en.tex file. The vulnerability is fixed in commit 91f5e6b.
vllm-project vllm version v0.6.2 contains a vulnerability in the MessageQueue.dequeue() API function. The function uses pickle.loads to parse received sockets directly, leading to a remote code execution vulnerability. An attacker can exploit this by sending a malicious payload to the MessageQueue, causing the victim's machine to execute arbitrary code.
An open redirect vulnerability in automatic1111/stable-diffusion-webui version 1.10.0 allows a remote unauthenticated attacker to redirect users to arbitrary websites via a specially crafted URL. This vulnerability can be exploited to conduct phishing attacks, distribute malware, and steal user credentials.
A Cross-Site WebSocket Hijacking (CSWSH) vulnerability in automatic1111/stable-diffusion-webui version 1.10.0 allows an attacker to clone a malicious server extension from a GitHub repository. The vulnerability arises from the lack of proper validation on WebSocket connections at ws://127.0.0.1:7860/queue/join, enabling unauthorized actions on the server. This can lead to unauthorized cloning of server extensions, execution of malicious scripts, data exfiltration, and potential denial of service (DoS).
An Insecure Direct Object Reference (IDOR) vulnerability exists in the `PATCH /v1/runs/:id/score` endpoint of lunary-ai/lunary version 1.6.0. This vulnerability allows an attacker to update the score data of any run by manipulating the id parameter in the request URL, which corresponds to the `runId_score` in the database. The endpoint does not sufficiently validate whether the authenticated user has permission to modify the specified runId, enabling an attacker with a valid account to modify other users' runId scores by specifying different id values. This issue was fixed in version 1.6.1.
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.