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I will audit and harden ai generated python automation code
Pablo
About this gig
Have an AI-generated Python script or small automation that needs a careful review before you rely on it?
I review one bounded Python automation, identify concrete defects and validation gaps, apply the agreed low-risk hardening, and return a readable handoff with verification notes.
Depending on the package, I can review inputs, outputs, validation, duplicate handling, exceptions, and assumptions; add or update deterministic tests; apply small fixes; and document remaining risks and how to run the result.
This is functional and maintainability-oriented work within the selected package. It is not penetration testing, security certification, a full rewrite, deployment, monitoring, or a production guarantee. Please send sanitized code and sample data. Do not send passwords, API keys, or confidential personal data.
My related portfolio example uses synthetic CSV/JSON data, validation, provenance, and automated tests; it is a demonstration, not paid client work.
Get to know Pablo
Pablo
Mechanical Engineering, Python, Excel, and Technical Automation
- FromSpain
- Member sinceSep 2026
- Avg. response time1 hour
Languages
Spanish, Galician, English
I'm a mechanical engineering student who turns calculations, spreadsheet work, and technical data into practical tools. I use Python and Excel for automation, data cleanup, validation, reporting, and documentation.
During my engineering internship, I developed a Python simulation tool for gaseous-hydrogen systems, covering thermodynamics, compressible flow, piping, vessels, restrictions, validation, and Excel inputs and outputs.
I can help with engineering calculators, Excel/Python automation, CSV cleanup, reporting, and documentation. I deliver scoped, tested work with a practical handover.
Other Software Development Services I Offer
FAQ
Can you review any AI generated application?
This offer is for one bounded Python script or small repository slice. Larger applications, multiple services, or other languages need a separate scope review.
Will you fix every issue?
No. Each package includes only its stated number of bounded changes. Additional findings can be documented for later work.
Is this a security audit?
No. It is a functional and maintainability oriented review within package limits, not penetration testing, compliance certification, or a formal security assessment.
What data should I provide?
Provide sanitized source code, the Python version, setup instructions, sample inputs, expected outputs, and known failure cases. Do not send passwords, API keys, or confidential data.
Can you make the code production ready?
No guarantee is made. Deployment, monitoring, credentials, infrastructure, and production acceptance remain outside the package.
Does this include API or n8n work?
Not by default. External API and n8n work must be explicitly scoped as a separate bounded integration or workflow.
Is the portfolio example client work?
No. It uses synthetic data and is clearly a demonstration, not paid client work.
