pacheco973008-ops/portifolio1

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https://github.com/pacheco973008-ops/portifolio1.git · scanned 2026-05-27 21:09 UTC (1 week, 1 day ago) · 10 languages

21 findings (7 legacy + 14 scanner) 16th percentile · Python · tiny (<2K LoC) Scanner says 66 (lower by 23)

File as issue Image v2 schema

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 week, 1 day ago · v2 · 14 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

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Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	30.0	0.15	4.50
`security_score`	100.0	0.25	25.00
`testing_score`	0.0	0.20	0.00
`documentation_score`	10.0	0.15	1.50
`practices_score`	30.0	0.15	4.50
`code_quality`	80.0	0.10	8.00
Overall		1.00	43.5

Severity distribution — click a segment to filter

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Severity: Critical 0 High 1 Medium 5 Low 3 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 7 9-layer 7 Crowd 0 Layer: Quality 8 Frontend 1 Security 3 Cicd 1 Api 1

Exclude dismissed / FP Exclude test files

Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Fragile runtime 3 findings

What it is: Code that runs but breaks under predictable input — division by zero, missing keys, unbounded loops, off-by-one slicing.

Why it matters: Reaches production undetected because happy-path tests pass. First user with a weird input crashes the request.

How AI causes it: AI loves writing the happy path; doesn't probe edge cases unless explicitly asked.

Fix approach: Add property-based tests. Wrap external inputs with explicit validators. Use the framework's typed deserializer (Pydantic, attrs).

3 matching findings on this repo

medium [SEC123] Production stack trace / debug output exposed: Debug mode left on in p… main.py:22
info [MINED069] Debug True Prod: Django/Flask DEBUG=True or app.debug=True in non-te… main.py:22
high [SEC135] Auth/permission check missing on AI-generated endpoint: Mutating HTTP … main.py:15

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Config drift 1 finding

What it is: Settings duplicated across env files, Docker compose, K8s, and code defaults, all with slightly different values.

Why it matters: Production behaviour depends on whichever copy your loader reads first. Subtle bugs in staging that don't reproduce in dev.

How AI causes it: AI writes new config from memory rather than reading the existing source.

Fix approach: Pick one source of truth (env vars + a settings module). Have every other place import from there. Lint for duplicates in CI.

1 matching finding on this repo

medium No CI/CD configuration found

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