A vulnerability in the `download_model_with_test_data` function of the onnx/onnx framework, version 1.16.0, allows for arbitrary file overwrite due to inadequate prevention of path traversal attacks in malicious tar files. This vulnerability enables attackers to overwrite any file on the system, potentially leading to remote code execution, deletion of system, personal, or application files, thus impacting the integrity and availability of the system. The issue arises from the function's handling of tar file extraction without performing security checks on the paths within the tar file, as demonstrated by the ability to overwrite the `/home/kali/.ssh/authorized_keys` file by specifying an absolute path in the malicious tar file.

A Server-Side Request Forgery (SSRF) vulnerability exists in the file upload section of imartinez/privategpt version 0.5.0. This vulnerability allows attackers to send crafted requests that could result in unauthorized access to the local network and potentially sensitive information. Specifically, by manipulating the 'path' parameter in a file upload request, an attacker can cause the application to make arbitrary requests to internal services, including the AWS metadata endpoint. This issue could lead to the exposure of internal servers and sensitive data.

In lunary-ai/lunary version 1.2.4, an account takeover vulnerability exists due to the exposure of password recovery tokens in API responses. Specifically, when a user initiates the password reset process, the recovery token is included in the response of the `GET /v1/users/me/org` endpoint, which lists all users in a team. This allows any authenticated user to capture the recovery token of another user and subsequently change that user's password without consent, effectively taking over the account. The issue lies in the inclusion of the `recovery_token` attribute in the users object returned by the API.

In lunary-ai/lunary version 1.2.2, a business logic error allows users to bypass the intended limitations on team member invitations and additions, regardless of their subscription plan. The vulnerability arises due to the lack of validation against the predefined member limits in the SEAT_ALLOWANCE constants during the invitation and joining processes. This issue enables users on any plan, including the free plan, to invite and add more members to a team than allowed, effectively circumventing the system's subscription model. The flaw is located in the backend's handling of user invitations and additions, specifically in the /api/v1/auth/index.ts and /api/v1/users.ts endpoints, where the system fails to check the current number of team members against the allowed limits before proceeding with the invitation and addition operations.

An Improper Access Control vulnerability exists in the lunary-ai/lunary repository, affecting versions up to and including 1.2.2. The vulnerability allows unauthorized users to view any prompts in any projects by supplying a specific prompt ID to an endpoint that does not adequately verify the ownership of the prompt ID. This issue was fixed in version 1.2.25.

An Incorrect Authorization vulnerability exists in lunary-ai/lunary versions up to and including 1.2.2, which allows unauthenticated users to delete any dataset. The vulnerability is due to the lack of proper authorization checks in the dataset deletion endpoint. Specifically, the endpoint does not verify if the provided project ID belongs to the current user, thereby allowing any dataset to be deleted without proper authentication. This issue was fixed in version 1.2.8.

A Privilege Escalation Vulnerability exists in lunary-ai/lunary version 1.2.2, where any user can delete any datasets due to missing authorization checks. The vulnerability is present in the dataset deletion functionality, where the application fails to verify if the user requesting the deletion has the appropriate permissions. This allows unauthorized users to send a DELETE request to the server and delete any dataset by specifying its ID. The issue is located in the datasets.delete function within the datasets index file.

An Insecure Direct Object Reference (IDOR) vulnerability was identified in lunary-ai/lunary, affecting versions up to and including 1.2.2. This vulnerability allows unauthorized users to view, update, or delete any dataset_prompt or dataset_prompt_variation within any dataset or project. The issue stems from improper access control checks in the dataset management endpoints, where direct references to object IDs are not adequately secured against unauthorized access. This vulnerability was fixed in version 1.2.25.

An improper access control vulnerability exists in the lunary-ai/lunary repository, specifically within the versions.patch functionality for updating prompts. Affected versions include 1.2.2 up to but not including 1.2.25. The vulnerability allows unauthorized users to update prompt details due to insufficient access control checks. This issue was addressed and fixed in version 1.2.25.

A timing attack vulnerability exists in the gaizhenbiao/chuanhuchatgpt repository, specifically within the password comparison logic. The vulnerability is present in version 20240310 of the software, where passwords are compared using the '=' operator in Python. This method of comparison allows an attacker to guess passwords based on the timing of each character's comparison. The issue arises from the code segment that checks a password for a particular username, which can lead to the exposure of sensitive information to an unauthorized actor. An attacker exploiting this vulnerability could potentially guess user passwords, compromising the security of the system.

A blind SQL injection vulnerability exists in the berriai/litellm application, specifically within the '/team/update' process. The vulnerability arises due to the improper handling of the 'user_id' parameter in the raw SQL query used for deleting users. An attacker can exploit this vulnerability by injecting malicious SQL commands through the 'user_id' parameter, leading to potential unauthorized access to sensitive information such as API keys, user information, and tokens stored in the database. The affected version is 1.27.14.

BerriAI's litellm, in its latest version, is vulnerable to arbitrary file deletion due to improper input validation on the `/audio/transcriptions` endpoint. An attacker can exploit this vulnerability by sending a specially crafted request that includes a file path to the server, which then deletes the specified file without proper authorization or validation. This vulnerability is present in the code where `os.remove(file.filename)` is used to delete a file, allowing any user to delete critical files on the server such as SSH keys, SQLite databases, or configuration files.

A path traversal vulnerability exists in the parisneo/lollms application, affecting version 9.4.0 and potentially earlier versions, but fixed in version 5.9.0. The vulnerability arises due to improper validation of file paths between Windows and Linux environments, allowing attackers to traverse beyond the intended directory and read any file on the Windows system. Specifically, the application fails to adequately sanitize file paths containing backslashes (`\`), which can be exploited to access the root directory and read, or even delete, sensitive files. This issue was discovered in the context of the `/user_infos` endpoint, where a crafted request using backslashes to reference a file (e.g., `\windows\win.ini`) could result in unauthorized file access. The impact of this vulnerability includes the potential for attackers to access sensitive information such as environment variables, database files, and configuration files, which could lead to further compromise of the system.

A Server-Side Request Forgery (SSRF) vulnerability exists in the stangirard/quivr application, version 0.0.204, which allows attackers to access internal networks. The vulnerability is present in the crawl endpoint where the 'url' parameter can be manipulated to send HTTP requests to arbitrary URLs, thereby facilitating SSRF attacks. The affected code is located in the backend/routes/crawl_routes.py file, specifically within the crawl_endpoint function. This issue could allow attackers to interact with internal services that are accessible from the server hosting the application.

A remote code execution (RCE) vulnerability exists in the '/install_extension' endpoint of the parisneo/lollms-webui application, specifically within the `@router.post("/install_extension")` route handler. The vulnerability arises due to improper handling of the `name` parameter in the `ExtensionBuilder().build_extension()` method, which allows for local file inclusion (LFI) leading to arbitrary code execution. An attacker can exploit this vulnerability by crafting a malicious `name` parameter that causes the server to load and execute a `__init__.py` file from an arbitrary location, such as the upload directory for discussions. This vulnerability affects the latest version of parisneo/lollms-webui and can lead to remote code execution without requiring user interaction, especially when the application is exposed to an external endpoint or operated in headless mode.

A path traversal vulnerability exists in the parisneo/lollms application, specifically within the `sanitize_path_from_endpoint` and `sanitize_path` functions in `lollms_core\lollms\security.py`. This vulnerability allows for arbitrary file reading when the application is running on Windows. The issue arises due to insufficient sanitization of user-supplied input, enabling attackers to bypass the path traversal protection mechanisms by crafting malicious input. Successful exploitation could lead to unauthorized access to sensitive files, information disclosure, and potentially a denial of service (DoS) condition by including numerous large or resource-intensive files. This vulnerability affects the latest version prior to 9.6.

man-group/dtale version 3.10.0 is vulnerable to an authentication bypass and remote code execution (RCE) due to improper input validation. The vulnerability arises from a hardcoded `SECRET_KEY` in the flask configuration, allowing attackers to forge a session cookie if authentication is enabled. Additionally, the application fails to properly restrict custom filter queries, enabling attackers to execute arbitrary code on the server by bypassing the restriction on the `/update-settings` endpoint, even when `enable_custom_filters` is not enabled. This vulnerability allows attackers to bypass authentication mechanisms and execute remote code on the server.

In gaizhenbiao/chuanhuchatgpt, specifically the version tagged as 20240121, there exists a vulnerability due to improper access control mechanisms. This flaw allows an authenticated attacker to bypass intended access restrictions and read the `history` files of other users, potentially leading to unauthorized access to sensitive information. The vulnerability is present in the application's handling of access control for the `history` path, where no adequate mechanism is in place to prevent an authenticated user from accessing another user's chat history files. This issue poses a significant risk as it could allow attackers to obtain sensitive information from the chat history of other users.

A stored Cross-Site Scripting (XSS) vulnerability existed in version (20240121) of gaizhenbiao/chuanhuchatgpt due to inadequate sanitization and validation of model output data. Despite user-input validation efforts, the application fails to properly sanitize or validate the output from the model, allowing for the injection and execution of malicious JavaScript code within the context of a user's browser. This vulnerability can lead to the execution of arbitrary JavaScript code in the context of other users' browsers, potentially resulting in the hijacking of victims' browsers.

A path traversal vulnerability exists in the 'cyber_security/codeguard' native personality of the parisneo/lollms-webui, affecting versions up to 9.5. The vulnerability arises from the improper limitation of a pathname to a restricted directory in the 'process_folder' function within 'lollms-webui/zoos/personalities_zoo/cyber_security/codeguard/scripts/processor.py'. Specifically, the function fails to properly sanitize user-supplied input for the 'code_folder_path', allowing an attacker to specify arbitrary paths using '../' or absolute paths. This flaw leads to arbitrary file read and overwrite capabilities in specified directories without limitations, posing a significant risk of sensitive information disclosure and unauthorized file manipulation.