VAITP

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 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 — or entirely absent — 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.

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.

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.

A code injection vulnerability exists in baryhuang/mcp-server-aws-resources-python 0.1.0 that allows remote code execution through insufficient input validation in the execute_query method. The vulnerability stems from the exposure of dangerous Python built-in functions (__import__, getattr, hasattr) in the execution namespace and the direct use of exec() to execute user-supplied code. An attacker can craft malicious queries to execute arbitrary Python code, leading to AWS credential theft (AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY), file system access, environment variable disclosure, and potential system compromise. The vulnerability allows attackers to bypass intended security controls and gain unauthorized access to sensitive AWS resources and credentials stored in the server's environment.

A command injection vulnerability exists in the MCP Data Science Server's (reading-plus-ai/mcp-server-data-exploration) 0.1.6 in the safe_eval() function (src/mcp_server_ds/server.py:108). The function uses Python's exec() to execute user-supplied scripts but fails to restrict the __builtins__ dictionary in the globals parameter. When __builtins__ is not explicitly defined, Python automatically provides access to all built-in functions including __import__, exec, eval, and open. This allows an attacker to execute arbitrary Python code with full system privileges, leading to complete system compromise. The vulnerability can be exploited by submitting a malicious script to the run_script tool, requiring no authentication or special privileges.

MaxKB is an open-source AI assistant for enterprise. In versions prior to 2.3.1, a user can get sensitive informations by Python code in tool module, although the process run in sandbox. Version 2.3.1 fixes the issue.

MaxKB is an open-source AI assistant for enterprise. In versions prior to 2.3.1, a user can access internal network services such as databases through Python code in the tool module, although the process runs in a sandbox. Version 2.3.1 fixes the issue.

Improper input validation in OneFlow v0.9.0 allows attackers to cause a segmentation fault via adding a Python sequence to the native code during broadcasting/type conversion.

An issue in AWS Wrappers for Amazon Aurora PostgreSQL may allow for privilege escalation to rds_superuser role. A low privilege authenticated user can create a crafted function that could be executed with permissions of other Amazon Relational Database Service (RDS) users. We recommend customers upgrade to the following versions: AWS JDBC Wrapper to v2.6.5, AWS Go Wrapper to 2025-10-17, AWS NodeJS Wrapper to v2.0.1, AWS Python Wrapper to v1.4.0 and AWS PGSQL ODBC driver to v1.0.1