VAITP

NiceGUI is a Python-based UI framework. Prior to 3.7.0, NiceGUI's FileUpload.name property exposes client-supplied filename metadata without sanitization, enabling path traversal when developers use the pattern UPLOAD_DIR / file.name. Malicious filenames containing ../ sequences allow attackers to write files outside intended directories, with potential for remote code execution through application file overwrites in vulnerable deployment patterns. This design creates a prevalent security footgun affecting applications following common community patterns. Note: Exploitation requires application code incorporating file.name into filesystem paths without sanitization. Applications using fixed paths, generated filenames, or explicit sanitization are not affected. This vulnerability is fixed in 3.7.0.

NiceGUI is a Python-based UI framework. The ui.markdown() component uses the markdown2 library to convert markdown content to HTML, which is then rendered via innerHTML. By default, markdown2 allows raw HTML to pass through unchanged. This means that if an application renders user-controlled content through ui.markdown(), an attacker can inject malicious HTML containing JavaScript event handlers. Unlike other NiceGUI components that render HTML (ui.html(), ui.chat_message(), ui.interactive_image()), the ui.markdown() component does not provide or require a sanitize parameter, leaving applications vulnerable to XSS attacks. This vulnerability is fixed in 3.7.0.

EPyT-Flow is a Python package designed for the easy generation of hydraulic and water quality scenario data of water distribution networks. Prior to 0.16.1, EPyT-Flow’s REST API parses attacker-controlled JSON request bodies using a custom deserializer (my_load_from_json) that supports a type field. When type is present, the deserializer dynamically imports an attacker-specified module/class and instantiates it with attacker-supplied arguments. This allows invoking dangerous classes such as subprocess.Popen, which can lead to OS command execution during JSON parsing. This also affects the loading of JSON files. This vulnerability is fixed in 0.16.1.

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 0.0.26 to before 1.56.0, aServer-Side Request Forgery (SSRF) vulnerability exists in Pydantic AI's URL download functionality. When applications accept message history from untrusted sources, attackers can include malicious URLs that cause the server to make HTTP requests to internal network resources, potentially accessing internal services or cloud credentials. This vulnerability only affects applications that accept message history from external users. This vulnerability is fixed in 1.56.0.

Pydantic AI is a Python agent framework for building applications and workflows with Generative AI. From 1.34.0 to before 1.51.0, a path traversal vulnerability in the Pydantic AI web UI allows an attacker to serve arbitrary JavaScript in the context of the application by crafting a malicious URL. In affected versions, the CDN URL is constructed using a version query parameter from the request URL. This parameter is not validated, allowing path traversal sequences that cause the server to fetch and serve attacker-controlled HTML/JavaScript from an arbitrary source on the same CDN, instead of the legitimate chat UI package. If a victim clicks the link or visits it via an iframe, attacker-controlled code executes in their browser, enabling theft of chat history and other client-side data. This vulnerability only affects applications that use Agent.to_web to serve a chat interface and clai web to serve a chat interface from the CLI. These are typically run locally (on localhost), but may also be deployed on a remote server. This vulnerability is fixed in 1.51.0.

n8n is an open source workflow automation platform. Prior to version 2.4.8, a vulnerability in the Python Code node allows authenticated users to break out of the Python sandbox environment and execute code outside the intended security boundary. This issue has been patched in version 2.4.8.

Boltz 2.0.0 contains an insecure deserialization vulnerability in its molecule loading functionality. The application uses Python pickle to deserialize molecule data files without validation. An attacker with the ability to place a malicious pickle file in a directory processed by boltz can achieve arbitrary code execution when the file is loaded.

pdfminer.six before 20251230 contains an insecure deserialization vulnerability in the CMap loading mechanism. The library uses Python pickle to deserialize CMap cache files without validation. An attacker with the ability to place a malicious pickle file in a location accessible to the application can trigger arbitrary code execution or privilege escalation when the file is loaded by a trusted process. This is caused by an incomplete patch to CVE-2025-64512.

Amazon SageMaker Python SDK before v3.1.1 or v2.256.0 disables TLS certificate verification for HTTPS connections made by the service when a Triton Python model is imported, incorrectly allowing for requests with invalid and self-signed certificates to succeed.

The Amazon SageMaker Python SDK before v3.2.0 and v2.256.0 includes the ModelBuilder HMAC signing key in the cleartext response elements of the DescribeTrainingJob function. A third party with permissions to both call this API and permissions to modify objects in the Training Jobs S3 output location may have the ability to upload arbitrary artifacts which are executed the next time the Training Job is invoked.