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90 of your 113 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.

Scan timing: clone 3.18s · analysis 1.88s · 2.9 MB · GitHub preflight 467ms

imakris/sintra

https://github.com/imakris/sintra.git · scanned 2026-05-19 20:32 UTC (2 weeks, 2 days ago) · 10 languages

215 findings (113 legacy + 102 scanner) 83rd percentile · Cpp · medium (20-100K LoC) Scanner says 88 (lower by 11)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 weeks, 2 days ago · v2 · 164 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

JSON
Combined
81.7
/100
Repobility
76
113 legacy
9-layer
88
66.7% cov · 51 gaps
Critical
7
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 55.0 0.15 8.25
security_score 95.0 0.25 23.75
testing_score 85.0 0.20 17.00
documentation_score 90.0 0.15 13.50
practices_score 70.0 0.15 10.50
code_quality 37.4 0.10 3.74
Overall 1.00 76.7
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 7 High 94 Medium 19 Low 31 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 113 9-layer 51 Crowd 0 Layer: Security 5 Quality 82 Software 35 Api 1 Frontend 1 Cicd 40

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 80 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 tests/runner/platform/windows.py:220
  • medium Bare except continues silently tests/runner/platform/windows.py:212
  • medium Bare except continues silently tests/runner/platform/windows.py:198
  • medium Bare except continues silently tests/runner/platform/windows.py:90
  • medium Bare except continues silently tests/runner/platform/windows.py:40
  • medium Bare except continues silently tests/runner/platform/posix.py:327
  • medium Bare except continues silently tests/runner/platform/posix.py:322
  • medium Bare except continues silently tests/runner/platform/posix.py:314
  • medium Bare except continues silently tests/runner/platform/posix.py:296
  • medium Bare except continues silently tests/runner/platform/posix.py:187
  • medium Bare except continues silently tests/runner/platform/posix.py:122
  • medium Bare except continues silently tests/runner/platform/posix.py:51
View all fragile runtime findings →
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 (11 lines) in tests/run_tests.py:122
View all commented-out code findings →
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