Denial of Service in urllib3 due to an unbounded decompression chain.
urllib3 is a user-friendly HTTP client library for Python. Starting in version 1.24 and prior to 2.6.0, the number of links in the decompression chain was unbounded allowing a malicious server to insert a virtually unlimited number of compression steps leading to high CPU usage and massive memory allocation for the decompressed data. This vulnerability is fixed in 2.6.0.
DNS rebinding in the MCP SDK allows malicious sites to access local servers.
The MCP Python SDK, called `mcp` on PyPI, is a Python implementation of the Model Context Protocol (MCP). Prior to version 1.23.0, tThe Model Context Protocol (MCP) Python SDK does not enable DNS rebinding protection by default for HTTP-based servers. When an HTTP-based MCP server is run on localhost without authentication using FastMCP with streamable HTTP or SSE transport, and has not configured TransportSecuritySettings, a malicious website could exploit DNS rebinding to bypass same-origin policy restrictions and send requests to the local MCP server. This could allow an attacker to invoke tools or access resources exposed by the MCP server on behalf of the user in those limited circumstances. Note that running HTTP-based MCP servers locally without authentication is not recommended per MCP security best practices. This issue does not affect servers using stdio transport. This vulnerability is fixed in 1.23.0.
vLLM RCE via model config's auto_map, ignoring `trust_remote_code=False`.
vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backendโs code on the victim host. This vulnerability is fixed in 0.11.1.
fontTools.varLib arbitrary file write via .designspace file leads to RCE.
fontTools is a library for manipulating fonts, written in Python. In versions from 4.33.0 to before 4.60.2, the fonttools varLib (or python3 -m fontTools.varLib) script has an arbitrary file write vulnerability that leads to remote code execution when a malicious .designspace file is processed. The vulnerability affects the main() code path of fontTools.varLib, used by the fonttools varLib CLI and any code that invokes fontTools.varLib.main(). This issue has been patched in version 4.60.2.
Keras get_file() path traversal in tar extraction allows arbitrary file write.
Keras version 3.11.3 is affected by a path traversal vulnerability in the keras.utils.get_file() function when extracting tar archives. The vulnerability arises because the function uses Python's tarfile.extractall() method without the security-critical filter='data' parameter. Although Keras attempts to filter unsafe paths using filter_safe_paths(), this filtering occurs before extraction, and a PATH_MAX symlink resolution bug triggers during extraction. This bug causes symlink resolution to fail due to path length limits, resulting in a security bypass that allows files to be written outside the intended extraction directory. This can lead to arbitrary file writes outside the cache directory, enabling potential system compromise or malicious code execution. The vulnerability affects Keras installations that process tar archives with get_file() and does not affect versions where this extraction method is secured with the appropriate filter parameter.
XSS in Spotipy's OAuth callback via the unsanitized `error` parameter.
Spotipy is a Python library for the Spotify Web API. Prior to version 2.25.2, there is a cross-site scripting (XSS) vulnerability in the OAuth callback server that allows for JavaScript injection through the unsanitized error parameter. Attackers can execute arbitrary JavaScript in the user's browser during OAuth authentication. This issue has been patched in version 2.25.2.
Insecure deserialization in Fugue's RPC server allows remote code execution.
Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites. In version 0.9.2 and prior, there is a remote code execution vulnerability by pickle deserialization via FlaskRPCServer. The Fugue framework implements an RPC server system for distributed computing operations. In the core functionality of the RPC server implementation, I found that the _decode() function in fugue/rpc/flask.py directly uses cloudpickle.loads() to deserialize data without any sanitization. This creates a remote code execution vulnerability when malicious pickle data is processed by the RPC server. The vulnerability exists in the RPC communication mechanism where the client can send arbitrary serialized Python objects that will be deserialized on the server side, allowing attackers to execute arbitrary code on the victim's machine. This issue has been patched via commit 6f25326.
LangChain prompt template injection allows access to Python internals.
LangChain is a framework for building agents and LLM-powered applications. From versions 0.3.79 and prior and 1.0.0 to 1.0.6, a template injection vulnerability exists in LangChain's prompt template system that allows attackers to access Python object internals through template syntax. This vulnerability affects applications that accept untrusted template strings (not just template variables) in ChatPromptTemplate and related prompt template classes. This issue has been patched in versions 0.3.80 and 1.0.7.
joserfc: Large JWT in error messages may cause DoS via excessive logging.
joserfc is a Python library that provides an implementation of several JSON Object Signing and Encryption (JOSE) standards. In versions from 1.3.3 to before 1.3.5 and from 1.4.0 to before 1.4.2, the ExceededSizeError exception messages are embedded with non-decoded JWT token parts and may cause Python logging to record an arbitrarily large, forged JWT payload. In situations where a misconfigured โ or entirely absent โ production-grade web server sits in front of a Python web application, an attacker may be able to send arbitrarily large bearer tokens in the HTTP request headers. When this occurs, Python logging or diagnostic tools (e.g., Sentry) may end up processing extremely large log messages containing the full JWT header during the joserfc.jwt.decode() operation. The same behavior also appears when validating claims and signature payload sizes, as the library raises joserfc.errors.ExceededSizeError() with the full payload embedded in the exception message. Since the payload is already fully loaded into memory at this stage, the library cannot prevent or reject it. This issue has been patched in versions 1.3.5 and 1.4.2.
Code injection in a Python component of Isaac-GR00T allows code execution.
NVIDIA Isaac-GR00T for all platforms contains a vulnerability in a Python component, where an attacker could cause a code injection issue. A successful exploit of this vulnerability might lead to code execution, escalation of privileges, information disclosure, and data tampering.
Introducing the "VAITP dataset": a specialized repository of Python vulnerabilities and patches, meticulously compiled for the use of the security research community. As Python's prominence grows, understanding and addressing potential security vulnerabilities become crucial. Crafted by and for the cybersecurity community, this dataset offers a valuable resource for researchers, analysts, and developers to analyze and mitigate the security risks associated with Python. Through the comprehensive exploration of vulnerabilities and corresponding patches, the VAITP dataset fosters a safer and more resilient Python ecosystem, encouraging collaborative advancements in programming security.
The supreme art of war is to subdue the enemy without fighting.
Sun Tzu – “The Art of War”
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