Over the past few months, I’ve been using AI tools (ChatGPT, Copilot, etc.) to generate Python code for small features and experiments.
It’s fast.
It’s convenient.
It often “looks correct.”
But I started noticing something uncomfortable.
A lot of AI-generated Python code includes patterns like:
SQL queries built with string concatenation
eval() used without restrictions
Direct file path concatenation
Hardcoded API keys
Unsafe os.system() usage
Nothing obviously broken.
But potentially insecure.
As someone experimenting with AI-assisted coding, I kept asking:
How do we quickly sanity-check AI-generated code before shipping it?
Manual review works — but it’s easy to miss things, especially for beginners.
So I built a small experiment called AICodeRisk.
It’s intentionally simple:
Paste Python code
It analyzes for common security vulnerabilities
Returns a structured JSON risk report
Includes severity, line numbers, and suggested fixes
No accounts.
No integrations.
Just paste → analyze → review.
You can try it here:
https://aicoderisk-v1.onrender.com/
This isn’t a product launch.
I’m validating whether this is even a real pain point.
I’m curious:
Do you trust AI-generated code by default?
Do you manually review everything?
Would you use a lightweight security sanity-check tool like this?
Or is this solving the wrong problem?
Brutal feedback welcome.
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