| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| Cursor is a code editor built for programming with AI. Versions 1.6 and below are vulnerable to Remote Code Execution (RCE) attacks through Visual Studio Code Workspaces. Workspaces allow users to open more than a single folder and save specific settings (pretty similar to .vscode/settings.json) for the folders / project. An untitled workspace is automatically created by VS Code (untitled.code-workspace), which contains all the folders and workspace settings from the user's current session, opening up an entire new attack vector if the user has a .code-workspace file in path (either untitled created automatically or a saved one). If an attacker is able to hijack the chat context of the victim (such as via a compromised MCP server), they can use prompt injection to make the Cursor Agent write into this file and modify the workspace. This leads to a bypass of CVE-2025-54130 which can lead to RCE by writing to the settings section. This issue is fixed in version 1.7. |
| Accela Automation Platform 22.2.3.0.230103 contains multiple vulnerabilities in the Test Script feature. An authenticated administrative user can execute arbitrary Java code on the server, resulting in remote code execution. In addition, improper input validation allows for arbitrary file write and server-side request forgery (SSRF), enabling interaction with internal or external systems. Successful exploitation can lead to full server compromise, unauthorized access to sensitive data, and further network exploitation. |
| Cursor is a code editor built for programming with AI. Versions 1.6.23 and below contain case-sensitive checks in the way Cursor IDE protects its sensitive files (e.g., */.cursor/mcp.json), which allows attackers to modify the content of these files through prompt injection and achieve remote code execution. A prompt injection can lead to full RCE through modifying sensitive files on case-insensitive fileystems. This issue is fixed in version 1.7. |
| Flowise is a drag & drop user interface to build a customized large language model flow. A file upload vulnerability in version 3.0.7 of FlowiseAI allows authenticated users to upload arbitrary files without proper validation. This enables attackers to persistently store malicious Node.js web shells on the server, potentially leading to Remote Code Execution (RCE). The system fails to validate file extensions, MIME types, or file content during uploads. As a result, malicious scripts such as Node.js-based web shells can be uploaded and stored persistently on the server. These shells expose HTTP endpoints capable of executing arbitrary commands if triggered. The uploaded shell does not automatically execute, but its presence allows future exploitation via administrator error or chained vulnerabilities. This presents a high-severity threat to system integrity and confidentiality. As of time of publication, no known patched versions are available. |
| This advisory addresses two critical security vulnerabilities present in Mautic versions before 5.2.3. These vulnerabilities could be exploited by authenticated users.
* Remote Code Execution (RCE) via Asset Upload: A Remote Code Execution vulnerability has been identified in the asset upload functionality. Insufficient enforcement of allowed file extensions allows an attacker to bypass restrictions and upload executable files, such as PHP scripts.
* Path Traversal File Deletion: A Path Traversal vulnerability exists in the upload validation process. Due to improper handling of path components, an authenticated user can manipulate the file deletion process to delete arbitrary files on the host system. |
| NiceHash QuickMiner 6.12.0 perform software updates over HTTP without validating digital signatures or hash checks. An attacker capable of intercepting or redirecting traffic to the update url and can hijack the update process and deliver arbitrary executables that are automatically executed, resulting in full remote code execution. This constitutes a critical supply chain attack vector. |
| AutoGPT versions 0.3.4 and earlier are vulnerable to a Server-Side Template Injection (SSTI) that could lead to Remote Code Execution (RCE). The vulnerability arises from the improper handling of user-supplied format strings in the `AgentOutputBlock` implementation, where malicious input is passed to the Jinja2 templating engine without adequate security measures. Attackers can exploit this flaw to execute arbitrary commands on the host system. The issue is fixed in version 0.4.0. |
| vllm-project vllm version 0.6.0 contains a vulnerability in the AsyncEngineRPCServer() RPC server entrypoints. The core functionality run_server_loop() calls the function _make_handler_coro(), which directly uses cloudpickle.loads() on received messages without any sanitization. This can result in remote code execution by deserializing malicious pickle data. |
| OpenWebUI version 0.3.0 contains a vulnerability in the audio API endpoint `/audio/api/v1/transcriptions` that allows for arbitrary file upload. The application performs insufficient validation on the `file.content_type` and allows user-controlled filenames, leading to a path traversal vulnerability. This can be exploited by an authenticated user to overwrite critical files within the Docker container, potentially leading to remote code execution as the root user. |
| mudler/LocalAI version 2.17.1 allows for arbitrary file write due to improper handling of automatic archive extraction. When model configurations specify additional files as archives (e.g., .tar), these archives are automatically extracted after downloading. This behavior can be exploited to perform a 'tarslip' attack, allowing files to be written to arbitrary locations on the server, bypassing checks that normally restrict files to the models directory. This vulnerability can lead to remote code execution (RCE) by overwriting backend assets used by the server. |
| BerriAI/litellm version 1.40.12 contains a vulnerability that allows remote code execution. The issue exists in the handling of the 'post_call_rules' configuration, where a callback function can be added. The provided value is split at the final '.' mark, with the last part considered the function name and the remaining part appended with the '.py' extension and imported. This allows an attacker to set a system method, such as 'os.system', as a callback, enabling the execution of arbitrary commands when a chat response is processed. |
| A remote code execution (RCE) vulnerability exists in the lightning-ai/pytorch-lightning library version 2.2.1 due to improper handling of deserialized user input and mismanagement of dunder attributes by the `deepdiff` library. The library uses `deepdiff.Delta` objects to modify application state based on frontend actions. However, it is possible to bypass the intended restrictions on modifying dunder attributes, allowing an attacker to construct a serialized delta that passes the deserializer whitelist and contains dunder attributes. When processed, this can be exploited to access other modules, classes, and instances, leading to arbitrary attribute write and total RCE on any self-hosted pytorch-lightning application in its default configuration, as the delta endpoint is enabled by default. |
| gaizhenbiao/chuanhuchatgpt is vulnerable to an unrestricted file upload vulnerability due to insufficient validation of uploaded file types in its `/upload` endpoint. Specifically, the `handle_file_upload` function does not sanitize or validate the file extension or content type of uploaded files, allowing attackers to upload files with arbitrary extensions, including HTML files containing XSS payloads and Python files. This vulnerability, present in the latest version as of 20240310, could lead to stored XSS attacks and potentially result in remote code execution (RCE) on the server hosting the application. |
| A vulnerability in binary-husky/gpt_academic version git 310122f allows for remote code execution. The application supports the extraction of user-provided RAR files without proper validation. The Python rarfile module, which supports symlinks, can be exploited to perform arbitrary file writes. This can lead to remote code execution by writing to sensitive files such as SSH keys, crontab files, or the application's own code. |
| In kedro-org/kedro version 0.19.8, the `pull_package()` API function allows users to download and extract micro packages from the Internet. However, the function `project_wheel_metadata()` within the code path can execute the `setup.py` file inside the tar file, leading to remote code execution (RCE) by running arbitrary commands on the victim's machine. |
| In the `manim` plugin of binary-husky/gpt_academic, versions prior to the fix, a vulnerability exists due to improper handling of user-provided prompts. The root cause is the execution of untrusted code generated by the LLM without a proper sandbox. This allows an attacker to perform remote code execution (RCE) on the app backend server by injecting malicious code through the prompt. |
| In eosphoros-ai/db-gpt version v0.6.0, the web API `POST /v1/personal/agent/upload` is vulnerable to Arbitrary File Upload with Path Traversal. This vulnerability allows unauthorized attackers to upload arbitrary files to the victim's file system at any location. The impact of this vulnerability includes the potential for remote code execution (RCE) by writing malicious files, such as a malicious `__init__.py` in the Python's `/site-packages/` directory. |
| The `add_llm` function in `llm_app.py` in infiniflow/ragflow version 0.11.0 contains a remote code execution (RCE) vulnerability. The function uses user-supplied input `req['llm_factory']` and `req['llm_name']` to dynamically instantiate classes from various model dictionaries. This approach allows an attacker to potentially execute arbitrary code due to the lack of comprehensive input validation or sanitization. An attacker could provide a malicious value for 'llm_factory' that, when used as an index to these model dictionaries, results in the execution of arbitrary code. |
| A vulnerability in mlflow/mlflow version 8.2.1 allows for remote code execution due to improper neutralization of special elements used in an OS command ('Command Injection') within the `mlflow.data.http_dataset_source.py` module. Specifically, when loading a dataset from a source URL with an HTTP scheme, the filename extracted from the `Content-Disposition` header or the URL path is used to generate the final file path without proper sanitization. This flaw enables an attacker to control the file path fully by utilizing path traversal or absolute path techniques, such as '../../tmp/poc.txt' or '/tmp/poc.txt', leading to arbitrary file write. Exploiting this vulnerability could allow a malicious user to execute commands on the vulnerable machine, potentially gaining access to data and model information. The issue is fixed in version 2.9.0. |
| In the latest version of vanna-ai/vanna, the `vanna.ask` function is vulnerable to remote code execution due to prompt injection. The root cause is the lack of a sandbox when executing LLM-generated code, allowing an attacker to manipulate the code executed by the `exec` function in `src/vanna/base/base.py`. This vulnerability can be exploited by an attacker to achieve remote code execution on the app backend server, potentially gaining full control of the server. |
