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This article provides a balanced deep dive into the use of AI and Machine Learning for Python code security, questioning the current limitations of AI tools and emphasizing the continued vital role of human expertise in developing trustworthy security analyzers.
AI 生成摘要
本文深入探討了將AI與機器學習應用於Python程式碼安全性的現況，質疑現有AI工具的局限性，並強調人類專業知識在開發值得信賴的Python安全分析工具方面仍至關重要。
I love new technology. I also advocate for Free and Open Machine Learning/AI. I think FOSS AI/ML is crucial for everyone. See FOSS AI/ML Guide.
AI/Machine learning is an exciting and powerful technology. The continuous use and growth of AI and machine learning technology opens new opportunities. It also enables opportunities for solving complex problems in a more simple way.
For Python Code Audit we make use of AI/ML capabilities in a secure, safe and most ethical way possible.
In the view below is outlined how AI/ML technology is used for the development of Python Code Audit.Truth is: Most AI tools turned out to be of limited value for real trustworthy cybersecurity aspects. Human knowledge work, especially on design and security aspects is currently still vital for developing and maintaining a trustworthy Python security code analyzer!
If you do use 100% AI cyber solutions, you can be more vulnerable for security breaches instead of less.
100% AI Python cybersecurity solutions that are built upon LLMs for cybersecurity problems are still far from mature. HIDS systems (Host Intrusion Detection Systems) have a long history of applying ML technologies as well as spam-filters. Creating security products that ‘learns’ from patterns is not new for security. AI/ML technologies have been applied for many years for HIDS systems and spam-filters. Applying AI for cyber security has been done for many years with variable success.
IT hypes like AI, AI-agents and LLMs are not the holy grail for solving your cyber security problems.
In the end you always pay more for cyber security solutions, but the risks still remain.
Python Code Audit is an advanced, Python-specific Static Application Security Testing tool designed to analyse Python packages and source code for security vulnerabilities.
Installation
To install or upgrade to the latest version:
Once installed, Python Code Audit can immediately scan Python packages and projects.
Example scan
This command scans the ultrafastrss package directly from PyPI.org and generates a detailed HTML security report.
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