Exploit Intelligence Platform

pgAdmin <= 8.3 is affected by a path-traversal vulnerability while deserializing users’ sessions in the session handling code. If the server is running on Windows, an unauthenticated attacker can load and deserialize remote pickle objects and gain code execution. If the server is running on POSIX/Linux, an authenticated attacker can upload pickle objects, deserialize them, and gain code execution.

An issue in the component js2py.disable_pyimport() of js2py up to v0.74 allows attackers to execute arbitrary code via a crafted API call.

An issue in pyload-ng v0.5.0b3.dev85 running under python3.11 or below allows attackers to execute arbitrary code via a crafted HTTP request.

A Local File Inclusion (LFI) vulnerability was identified in mlflow/mlflow, specifically in version 2.9.2, which was fixed in version 2.11.3. This vulnerability arises from the application's failure to properly validate URI fragments for directory traversal sequences such as '../'. An attacker can exploit this flaw by manipulating the fragment part of the URI to read arbitrary files on the local file system, including sensitive files like '/etc/passwd'. The vulnerability is a bypass to a previous patch that only addressed similar manipulation within the URI's query string, highlighting the need for comprehensive validation of all parts of a URI to prevent LFI attacks.

Mocodo Mocodo Online 4.2.6 and below does not properly sanitize the sql_case input field in /web/generate.php, allowing remote attackers to execute arbitrary commands and potentially command injection, leading to remote code execution (RCE) under certain conditions.

Gradio is an open-source Python package designed for quick prototyping. This vulnerability relates to **Server-Side Request Forgery (SSRF)** in the `/queue/join` endpoint. Gradio’s `async_save_url_to_cache` function allows attackers to force the Gradio server to send HTTP requests to user-controlled URLs. This could enable attackers to target internal servers or services within a local network and possibly exfiltrate data or cause unwanted internal requests. Additionally, the content from these URLs is stored locally, making it easier for attackers to upload potentially malicious files to the server. This impacts users deploying Gradio servers that use components like the Video component which involve URL fetching. Users are advised to upgrade to `gradio>=5` to address this issue. As a workaround, users can disable or heavily restrict URL-based inputs in their Gradio applications to trusted domains only. Additionally, implementing stricter URL validation (such as allowinglist-based validation) and ensuring that local or internal network addresses cannot be requested via the `/queue/join` endpoint can help mitigate the risk of SSRF attacks.

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.

Cobbler, a Linux installation server that allows for rapid setup of network installation environments, has an improper authentication vulnerability starting in version 3.0.0 and prior to versions 3.2.3 and 3.3.7. `utils.get_shared_secret()` always returns `-1`, which allows anyone to connect to cobbler XML-RPC as user `''` password `-1` and make any changes. This gives anyone with network access to a cobbler server full control of the server. Versions 3.2.3 and 3.3.7 fix the issue.

Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.9.0 or newer, enabling a maliciously uploaded PyFunc model to run arbitrary code on an end user’s system when interacted with.

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 arbitrary code injection vulnerability in TensorFlow's Keras framework (<2.13) allows attackers to execute arbitrary code with the same permissions as the application using a model that allow arbitrary code irrespective of the application.

Pycel through 1.0b30, when operating on an untrusted spreadsheet, allows code execution via a crafted formula in a cell, such as one beginning with the =IF(A1=200, eval("__import__('os').system( substring.

Pymatgen (Python Materials Genomics) is an open-source Python library for materials analysis. A critical security vulnerability exists in the `JonesFaithfulTransformation.from_transformation_str()` method within the `pymatgen` library prior to version 2024.2.20. This method insecurely utilizes `eval()` for processing input, enabling execution of arbitrary code when parsing untrusted input. Version 2024.2.20 fixes this issue.

A remote code execution vulnerability exists in the create_conda_env function of the parisneo/lollms repository, version 5.9.0. The vulnerability arises from the use of shell=True in the subprocess.Popen function, which allows an attacker to inject arbitrary commands by manipulating the env_name and python_version parameters. This issue could lead to a serious security breach as demonstrated by the ability to execute the 'whoami' command among potentially other harmful commands.

langflow <=1.0.18 is vulnerable to Remote Code Execution (RCE) as any component provided the code functionality and the components run on the local machine rather than in a sandbox.

pgAdmin versions 8.11 and earlier are vulnerable to a security flaw in OAuth2 authentication. This vulnerability allows an attacker to potentially obtain the client ID and secret, leading to unauthorized access to user data.

The huggingface/transformers library is vulnerable to arbitrary code execution through deserialization of untrusted data within the `load_repo_checkpoint()` function of the `TFPreTrainedModel()` class. Attackers can execute arbitrary code and commands by crafting a malicious serialized payload, exploiting the use of `pickle.load()` on data from potentially untrusted sources. This vulnerability allows for remote code execution (RCE) by deceiving victims into loading a seemingly harmless checkpoint during a normal training process, thereby enabling attackers to execute arbitrary code on the targeted machine.

D-Tale is a visualizer for pandas data structures. Prior to version 3.16.1, users hosting D-Tale publicly can be vulnerable to remote code execution allowing attackers to run malicious code on the server. Users should upgrade to version 3.16.1 where the `update-settings` endpoint blocks the ability for users to update the `enable_custom_filters` flag. The only workaround for versions earlier than 3.16.1 is to only host D-Tale to trusted users.

Hugging Face Transformers MobileViTV2 Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vulnerability allows remote attackers to execute arbitrary code on affected installations of Hugging Face Transformers. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The specific flaw exists within the handling of configuration files. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of the current user. Was ZDI-CAN-24322.

Versions of the package langchain-experimental from 0.0.15 and before 0.0.21 are vulnerable to Arbitrary Code Execution when retrieving values from the database, the code will attempt to call 'eval' on all values. An attacker can exploit this vulnerability and execute arbitrary python code if they can control the input prompt and the server is configured with VectorSQLDatabaseChain. **Notes:** Impact on the Confidentiality, Integrity and Availability of the vulnerable component: Confidentiality: Code execution happens within the impacted component, in this case langchain-experimental, so all resources are necessarily accessible. Integrity: There is nothing protected by the impacted component inherently. Although anything returned from the component counts as 'information' for which the trustworthiness can be compromised. Availability: The loss of availability isn't caused by the attack itself, but it happens as a result during the attacker's post-exploitation steps. Impact on the Confidentiality, Integrity and Availability of the subsequent system: As a legitimate low-privileged user of the package (PR:L) the attacker does not have more access to data owned by the package as a result of this vulnerability than they did with normal usage (e.g. can query the DB). The unintended action that one can perform by breaking out of the app environment and exfiltrating files, making remote connections etc. happens during the post exploitation phase in the subsequent system - in this case, the OS. AT:P: An attacker needs to be able to influence the input prompt, whilst the server is configured with the VectorSQLDatabaseChain plugin.