Improper certificate host validation in Apache Thrift Python bindings.
Improper Validation of Certificate with Host Mismatch vulnerability in Apache Thrift Python bindings. This issue affects Apache Thrift: before 0.24.0. Users are recommended to upgrade to version 0.24.0, which fixes the issue. This replaces CVE-2026-41603
A data amplification vulnerability in Apache Thrift may lead to Denial of Service.
Improper Handling of Highly Compressed Data (Data Amplification) vulnerability in Apache Thrift C++, Java, Python, Go, D, C/GLib bindings. This issue affects Apache Thrift: before 0.24.0. Users are recommended to upgrade to version 0.24.0, which fixes the issue.
Infinite loop in Apache Thrift language bindings can cause a Denial of Service.
Loop with Unreachable Exit Condition ('Infinite Loop') vulnerability in Apache Thrift Python, Go, PHP and Java bindings.This issue affects Apache Thrift: before 0.24.0. Users are recommended to upgrade to version 0.24.0, which fixes the issue.
Data amplification vulnerability in Apache Thrift Python may lead to DoS.
Improper Handling of Highly Compressed Data (Data Amplification) vulnerability in Apache Thrift Python bindings. This issue affects Apache Thrift: before 0.24.0. Users are recommended to upgrade to version 0.24.0, which fixes the issue.
Code injection via a crafted customBasePath allows remote code execution.
datamodel-code-generator prior to version 0.70.0 contains a code injection vulnerability that allows attackers who control input schemas to achieve remote code execution by supplying a malicious customBasePath value containing embedded newlines and a dot-free Python expression. The crafted value is emitted verbatim into a generated 'from ... import ...' statement without identifier validation, causing arbitrary Python code to execute when the generated module is imported.
NLTK collocations eval injection allows code execution via CLI arguments.
NLTK (Natural Language Toolkit) before version 3.9.3 contains an eval injection vulnerability in the nltk.collocations module that allows an attacker who controls command-line arguments to execute arbitrary Python code. When collocations.py is invoked directly, the __main__ block passes command-line arguments directly to eval() as suffixes of BigramAssocMeasures without allowlist validation or sanitization, enabling an attacker to supply a Python expression that escapes the intended attribute lookup and executes arbitrary code including OS commands via the os module.
Command injection in Ironic Python Agent via the ntp_server parameter.
In OpenStack Ironic Python Agent through 11.6.0, a project-scoped user with the manager role can achieve arbitrary code execution on a running Ironic-Python-Agent via a maliciously constructed configuration, because the value of ntp_server is passed to a shell.
Malicious bootc container can extract download credentials in Ironic agent.
In OpenStack Ironic Python Agent through 11.5.0, a malicious bootc container, when deployed using ironic-python-agent, may be able to extract the credentials used to download it.
Command injection in AWS Bedrock AgentCore SDK via crafted package names.
Improper neutralization of argument delimiters in the install_packages() method in AWS Bedrock AgentCore Python SDK before 1.18.1 might allow a remote authenticated user to execute arbitrary commands within the Code Interpreter sandbox via crafted package name arguments. To mitigate this issue, users should upgrade to the patched version 1.18.1.
PraisonAI RCE via crafted YAML due to insufficient AST validation.
PraisonAI before 4.6.78 contains a remote code execution vulnerability in JobWorkflowExecutor._exec_inline_python() due to insufficient AST validation of workflow script steps. Attackers can create malicious YAML workflow files with import os statements followed by os.system() calls that bypass sandbox checks and execute arbitrary OS commands with process privileges.
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”
:: Shaping the future through research and ingenuity ::