xpikollah-man/brn-app

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Scan timing: clone 1.44s · analysis 0.09s · GitHub preflight 427ms

https://github.com/xpikollah-man/brn-app.git · scanned 2026-05-28 05:57 UTC (1 week, 1 day ago) · 10 languages

14 findings (6 legacy + 8 scanner) 0th percentile · Unknown · tiny (<2K LoC) Scanner says 88 (lower by 46)

File as issue Image v2 schema

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 week, 1 day ago · v2 · 10 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`	0.0	0.15	0.00
`practices_score`	30.0	0.15	4.50
`code_quality`	79.4	0.10	7.94
Overall		1.00	41.9

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 1 Medium 5 Low 1 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 6 9-layer 4 Crowd 0 Layer: Quality 7 Api 1 Security 1 Cicd 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 1 finding

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).

1 matching finding on this repo

low Duplicated implementation block across source files aps.jsx:1

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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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