| CVE |
Vendors |
Products |
Updated |
CVSS v3.1 |
| A vulnerability in szad670401/hyperlpr v3.0 allows for a Denial of Service (DoS) attack. The server fails to handle excessive characters appended to the end of multipart boundaries, regardless of the character used. This flaw can be exploited by sending malformed multipart requests with arbitrary characters at the end of the boundary, leading to excessive resource consumption and a complete denial of service for all users. The vulnerability is unauthenticated, meaning no user login or interaction is required for an attacker to exploit this issue. |
| gaizhenbiao/chuanhuchatgpt version git d4ec6a3 is affected by a local file inclusion vulnerability due to the use of the gradio component gr.JSON, which has a known issue (CVE-2024-4941). This vulnerability allows unauthenticated users to access arbitrary files on the server by uploading a specially crafted JSON file and exploiting the improper input validation in the handle_dataset_selection function. |
| An unauthenticated Denial of Service (DoS) vulnerability was identified in ChuanhuChatGPT version 20240918, which could be exploited by sending large data payloads using a multipart boundary. Although a patch was applied for CVE-2024-7807, the issue can still be exploited by sending data in groups with 10 characters in a line, with multiple lines. This can cause the system to continuously process these characters, resulting in prolonged unavailability of the service. The exploitation now requires low privilege if authentication is enabled due to a version upgrade in Gradio. |
| A Regular Expression Denial of Service (ReDoS) vulnerability exists in the gradio-app/gradio repository, affecting the gr.Datetime component. The affected version is git commit 98cbcae. The vulnerability arises from the use of a regular expression `^(?:\s*now\s*(?:-\s*(\d+)\s*([dmhs]))?)?\s*$` to process user input. In Python's default regex engine, this regular expression can take polynomial time to match certain crafted inputs. An attacker can exploit this by sending a crafted HTTP request, causing the gradio process to consume 100% CPU and potentially leading to a Denial of Service (DoS) condition on the server. |
| In h2oai/h2o-3 version 3.46.0.1, the `run_tool` command exposes classes in the `water.tools` package through the `ast` parser. This includes the `XGBoostLibExtractTool` class, which can be exploited to shut down the server and write large files to arbitrary directories, leading to a denial of service. |
| A vulnerability in the `/3/Parse` endpoint of h2oai/h2o-3 version 3.46.0.1 allows for a denial of service (DoS) attack. The endpoint uses a user-specified string to construct a regular expression, which is then applied to another user-specified string. By sending multiple simultaneous requests, an attacker can exhaust all available threads, leading to a complete denial of service. |
| In version 0.7.5 of danny-avila/LibreChat, there is an improper access control vulnerability. Users can share, use, and create prompts without being granted permission by the admin. This can break application logic and permissions, allowing unauthorized actions. |
| An arbitrary file deletion vulnerability exists in danny-avila/librechat version v0.7.5-rc2, specifically within the /api/files endpoint. This vulnerability arises from improper input validation, allowing path traversal techniques to delete arbitrary files on the server. Attackers can exploit this to bypass security mechanisms and delete files outside the intended directory, including critical system files, user data, or application resources. This vulnerability impacts the integrity and availability of the system. |
| In lunary-ai/lunary version 1.5.6, the `/v1/evaluators/` endpoint lacks proper access control, allowing any user associated with a project to fetch all evaluator data regardless of their role. This vulnerability permits low-privilege users to access potentially sensitive evaluation data. |
| In version 1.5.5 of lunary-ai/lunary, a vulnerability exists where admins, who do not have direct permissions to access billing resources, can change the permissions of existing users to include billing permissions. This can lead to a privilege escalation scenario where an administrator can manage billing, effectively bypassing the intended role-based access control. Only users with the 'owner' role should be allowed to invite members with billing permissions. This flaw allows admins to circumvent those restrictions, gaining unauthorized access and control over billing information, posing a risk to the organization’s financial resources. |
| An improper authorization vulnerability exists in lunary-ai/lunary version 1.5.5. The /users/me/org endpoint lacks adequate access control mechanisms, allowing unauthorized users to access sensitive information about all team members in the current organization. This vulnerability can lead to the disclosure of sensitive information such as names, roles, or emails to users without sufficient privileges, resulting in privacy violations and potential reconnaissance for targeted attacks. |
| In lunary-ai/lunary v1.5.0, improper privilege management in the models.ts file allows users with viewer roles to modify models owned by others. The PATCH endpoint for models does not have appropriate privilege checks, enabling low-privilege users to update models they should not have access to modify. This vulnerability could lead to unauthorized changes in critical resources, affecting the integrity and reliability of the system. |
| lunary-ai/lunary is vulnerable to broken access control in the latest version. An attacker can view the content of any dataset without any kind of authorization by sending a GET request to the /v1/datasets endpoint without a valid authorization token. |
| A vulnerability in haotian-liu/llava v1.2.0 allows an attacker to cause a Denial of Service (DoS) by appending a large number of characters to the end of a multipart boundary in a file upload request. This causes the server to continuously process each character, rendering the application inaccessible. |
| Horovod versions up to and including v0.28.1 are vulnerable to unauthenticated remote code execution. The vulnerability is due to improper handling of base64-encoded data in the `ElasticRendezvousHandler`, a subclass of `KVStoreHandler`. Specifically, the `_put_value` method in `ElasticRendezvousHandler` calls `codec.loads_base64(value)`, which eventually invokes `cloudpickle.loads(decoded)`. This allows an attacker to send a malicious pickle object via a PUT request, leading to arbitrary code execution on the server. |
| 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. |
| Realchar version v0.0.4 is vulnerable to an unauthenticated denial of service (DoS) attack. The vulnerability exists in the file upload request handling, where appending characters, such as dashes (-), to the end of a multipart boundary in an HTTP request causes the server to continuously process each character. This leads to excessive resource consumption and renders the service unavailable. The issue is unauthenticated and does not require any user interaction, impacting all users of the service. |
| A vulnerability in the `start_app_server` function of parisneo/lollms-webui V12 (Strawberry) allows for path traversal and OS command injection. The function does not properly sanitize the `app_name` parameter, enabling an attacker to upload a malicious `server.py` file and execute arbitrary code by exploiting the path traversal vulnerability. |
| 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. |
| A misconfiguration in the AndroidManifest.xml file in hamza417/inure before build97 allows for task hijacking. This vulnerability permits malicious applications to inherit permissions of the vulnerable app, potentially leading to the exposure of sensitive information. An attacker can create a malicious app that hijacks the legitimate Inure app, intercepting and stealing sensitive information when installed on the victim's device. This issue affects all Android versions before Android 11. |
