knjx547/patched_bunny

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Scan timing: clone 1.48s · analysis 0.19s · 0.1 MB · GitHub preflight 422ms

https://github.com/knjx547/patched_bunny.git · scanned 2026-05-29 06:45 UTC (1 week ago) · 10 languages

124 findings (66 legacy + 58 scanner) 11th percentile · Python · small (2-20K LoC) Scanner says 84 (lower by 41)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 week ago · v2 · 95 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`	40.0	0.15	6.00
`practices_score`	30.0	0.15	4.50
`code_quality`	37.0	0.10	3.70
Overall		1.00	43.7

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 70 Medium 7 Low 13 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 66 9-layer 29 Crowd 0 Layer: Quality 85 Software 5 Api 1 Frontend 1 Security 2 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 63 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).

12 matching findings on this repo

medium Bare except continues silently patched_bunny.py:481
medium Bare except continues silently patched_bunny.py:315
medium Bare except continues silently patched_bunny.py:306
medium Bare except continues silently patched_bunny.py:298
medium Bare except continues silently patched_bunny.py:289
medium Bare except continues silently patched_bunny.py:275
medium Bare except continues silently patched_bunny.py:269
medium Bare except continues silently patched_bunny.py:264
medium Bare except continues silently patched_bunny.py:121
medium Bare except continues silently patched_bunny.py:3079
medium Bare except continues silently patched_bunny.py:3055
medium Bare except continues silently patched_bunny.py:3030

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Commented-out code 1 finding

What it is: Lines of source that were intentionally disabled but never deleted.

Why it matters: Git already remembers history — commented code rots, becomes wrong, and adds noise to diffs.

How AI causes it: AI sometimes comments out broken code instead of fixing it. Reviewers approve out of inertia.

Fix approach: Delete. Trust `git log`. If you really need to remember, save it in a notes file under `docs/`.

1 matching finding on this repo

info Commented-code block (6 lines) in patched_bunny.py:911

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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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