While security testing is crucial for protection, identifying security defects in Python-based software requires specialised knowledge. Most security testers lack the in-depth training on Python-specific nuances that is essential for performing effective security evaluations.
In today’s digital world, cybersecurity remains a critical concern. This applies equally to the consumption and creation of Python software: preventing vulnerabilities begins with a robust architecture. However, even well-written code—including that generated by AI—is not secure by default. Python Code Audit is a vital, open-source (FOSS) tool that should be an integral part of your workflow.
I have worked on delivering large-scale IT systems for more than 25 years. I spent my early years as an engineer, and for the last 20 years, I have worked in various architecture roles, steering development and solving complex issues. But some things never change:Cybersecurity remains a difficult and complex field. It requires expertise across many different areas, such as business and computer sciences.
Almost all software is under attack today, yet many organisations remain unprepared in their defence. Every day, news emerges of computer systems being breached, frequently through vulnerabilities within the software itself.
On an almost daily basis, I see new Static Application Security Testing (SAST) tools emerging. Nearly all of these new solutions are powered by LLMs and offered exclusively as SaaS products.
Security is not a trivial matter. High-quality security tools are essential to protect your organisation. What is far more dangerous, however, are professional-looking cybersecurity tools that claim to deliver robust protection but, in reality, provide poor results. Tools of low quality do not just fail to protect you — they create a false sense of security. And that risk is enormous.
Defence in depth is a core security principle that relies on multiple, independent security controls. If one fails, others detect or mitigate the threat. In Python Static Application Security Testing (SAST), depending on a single scanner creates unnecessary risk and incomplete vulnerability coverage.
Static Application Security Testing (SAST) tools are essential, including when creating or using Python programs.
From a security-by-design perspective, ensuring that applications have no weaknesses that can be easily converted into vulnerabilities is more than just a best practice. SAST tools for Python empower developers, testers, and security teams to identify software weaknesses before code is deployed or exploited.
In today’s digital world, security remains a critical concern. This applies equally to Python software.Python is the most widely used programming language worldwide.
To use a Python SAST scanner (Static Application Security Testing Tool) effectively, it is vital to understand the difference between a weakness and a vulnerability:
Python’s dominance as a programming language makes it a prime target for security risks. Security is never guaranteed: a solid architecture helps, but even well-written code—including AI-generated code—is not secure by default.
The gold guiding principle for protecting your systems is simple: never trust, always verify (Zero Trust). Cybersecurity is inherently complex and mistakes are inevitable, proactive verification is an indispensable safeguard.
Python is the most widely used programming language worldwide. Many great Python programs and libraries are available on the official Python repository: PyPI.org.
Creating secure Python programs is a complex skill. So not all Python programs published on PyPI.org are created with security in mind and with the use of Python Secure Coding Guidelines. But before you install any Python program from PyPI.org with the simple command:
pip install <package-name>
You should validate the Python program or library on code weaknesses. This can be done with one simple command:
You may specify a custom name for the HTML report that will be created, but this is not necessary. Python Code Audit does not install the program; it analyses the Python code safely by making use of Python’s AST (Abstract Syntax Tree) technology.
Prerequisite
Before running the codeaudit command a prerequisite is that you have Python Code Audit installed. This can be done with a single command:
pip install -U codeaudit
Python Code Audit is an advanced SAST tool that automates the review of Python source code to identify potential security vulnerabilities. It is designed to be simple and safe to use, catering both to security specialists and to users who want to check possible risks in a Python program before installing and running it. The manual provides detailed explanations of any found code weaknesses. Depending on your context, you must decide whether the weaknesses found pose a risk, or if you are confident enough to install and run the program.
Adhering to a simple checklist is the most effective way to prevent security disasters when running Python programs. The complete checklist to help you mitigate security risks before executing any unknown or third-party Python program is provided below:
The release of Python 3.14, released on October 7, 2025, marks a great milestone for the Python programming language. Developing a new release for the Python language is a major challenge and very hard work for many volunteers active in the Python ecosystem.
Python 3.14.0 contains many new features and optimisations compared to Python 3.13.
