Fix/63 normalize category

[vikask011]

Linked issue

Closes #63

What this PR does

This PR introduces a centralized category normalization utility to ensure dependency-related findings are categorized consistently across different scanners. The OSV, Semgrep, and Gitleaks scanners were updated to use the shared normalization logic, and unit tests were added to verify the expected behavior.

Type of change

• Bug fix
• New feature
• ML model / training pipeline
• Refactor (no behaviour change)
• Documentation
• Tests only

ML tier (if applicable)

• Tier 1 — Triage
• Tier 2 — Predictive
• Tier 3 — Autonomous
• Not ML-related

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Changes

Backend

• Added a shared category normalization utility (categories.py).
• Updated OSV scanner to normalize dependency finding categories.
• Updated Semgrep scanner to use centralized category normalization.
• Updated Gitleaks scanner to use consistent category mapping.
• Added unit tests covering category normalization behavior.

New dependencies

• None.

Database / schema changes

• None.

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Testing

How did you test this?

• Ran the new category normalization unit tests locally.
• Tested the scanning workflow locally and verified findings were returned with normalized categories.
• Verified that OSV, Semgrep, and Gitleaks findings are categorized consistently.
• Confirmed no regressions in existing scanner behavior.

Checklist

• Tested locally end-to-end (upload ZIP or GitHub URL → scan → findings returned correctly)
• New ML model falls back gracefully when model file is absent
• No new console.error or unhandled Python exceptions introduced
• Added or updated tests where applicable
• requirements.txt / package.json updated if new dependencies added
• New model files (.pkl, .pt, etc.) are gitignored, not committed

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Anything reviewers should focus on

Please review the category normalization logic and ensure the mappings remain consistent across all scanners and existing finding classifications.

Screenshots (if UI changed)

Not applicable.

[Krishnx21]

Thanks for the contribution.

I found a few issues that should be addressed before merging:

• category is passed twice to the Finding constructor in multiple files, which will raise SyntaxError: keyword argument repeated: category.
• There are duplicate return out statements that result in unreachable code.
• Please verify that ml_features is defined before being used.

I've left inline comments with more details.

[ionfwsrijan]

@vikask011 Fix failing tests and mentor review

[ionfwsrijan]

@vikask011 Still failing checks. Join our dc server to connect with fellow contributors and mentors. Our mentors will help you out there.

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