What the Halting Problem Means for Python Security

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What the Halting Problem Means for Python Security<br>The Case for 100% Transparent, Open-Source Python SAST

Maikel<br>Jul 02, 2026

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100% accuracy security myth sketch

Python code plays a central role in modern computing, yet Python applications are not immune to cybersecurity threats. Consequently, security has become a critical concern for both users and developers alike.<br>But cybersecurity is never black or white. It is all about context. Being precise about definitions is key. A security weakness is not the same as a vulnerability. It always depends.<br>Static security testing, also known as Static Application Security Testing (SAST), is a methodology that analyses an application’s source code. The purpose is to identify potential security weaknesses before running the application. One of the greatest benefits of using a SAST scanner on any program before execution is that it saves enormous amounts of time and money, as preventing security and privacy disasters is far cheaper and less complex than fixing them later.<br>Performing a SAST before running a program is especially essential when executing Python programs written by others. Unfortunately, this is still not common practice. Most SAST scanners are too complex, require too much time for a quick package scan on PyPI, and are expensive to use. Worst of all, even expensive, commercial Python SAST scanners are far from perfect. In the best-case scenario, you will only be disappointed. In the worst, the risk of a false sense of security is enormous. That is why you should use a simple checklist before using any Python security testing tool.<br>To use a Python SAST scanner effectively, it is vital to make a clear distinction between a weakness and a vulnerability:<br>Weakness (or potential security issue): A weakness is a flaw, error, poor design choice, or unsafe programming practice in your code that might create security problems under certain conditions. It represents an increased risk, but it is not necessarily exploitable in your specific context.<br>Weaknesses do not constitute threats themselves. Instead, they provide opportunities for existing threats to exploit a system<br>Vulnerability: A vulnerability is a weakness that could be exploited by an attacker to compromise the confidentiality, integrity, or availability of your system.<br>Many SAST scanners are marketed as being able to identify vulnerabilities hidden in source code by using static analysis to determine whether a weakness may be exploitable. They often prioritise findings using heuristics and severity models based on code patterns rather than the application’s actual deployment context. This is inherently limited for two simple reasons:<br>A vulnerability is always context-dependent. No software has the ability to evaluate your entire environment (systems, networks, processes, and people), nor is it possible to feed software all of your defence-in-depth measures, which can be both technical and non-technical.

Security software that decides whether code is suspicious or not can and will fail. Software can never determine the intent of a statement based solely on syntax or coding rules.

A good example is checking exception statements in Python code for possible security issues. This is a necessary step, and a good Python SAST scanner should detect problematic exception handling for you. A simple example of a potentially problematic pattern is:<br>try:<br>do_some_stuff()<br>except Exception:<br>passThe use of pass and continue in Python exception handling cannot be classified as inherently secure or insecure through syntax alone. Even when using advanced static analysis techniques like taint analysis or “magic” AI tools, 100% accuracy is impossible.<br>Python is highly dynamic : it allows runtime behaviour that defeats full static modelling. This means the actual behaviour of a function may not be fully knowable at analysis time. At a deeper theoretical level, determining all possible runtime behaviours of arbitrary programs is undecidable. This is a consequence of the Halting Problem: no algorithm can correctly predict the behaviour of all programs in all cases.<br>This means that:<br>No static security analysis tool can always determine whether an exception suppression is safe, malicious, or just a coding error frequently seen in AI-generated Python code.

Many SAST tools rely on heuristics, but intent is not observable in code. Because heuristics are inherently imperfect, they produce false positives (flagging safe patterns) and false negatives (missing real issues).

One of the reasons we started Python Code Audit was to create a better Python SAST scanner. We want to prevent both false positives and false negatives at all times. This is why Python Code Audit reports “potential security issues” rather than definitive security weaknesses or vulnerabilities.<br>A security tool must be inherently...