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AurevLan/WhatIsUp

https://github.com/AurevLan/WhatIsUp · scanned 2026-06-17 01:17 UTC (1 month, 2 weeks ago)

112 raw signals (0 security + 112 graph)

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Complete repo analysis

Last scanned 1 month, 2 weeks ago · v2 · last Δ -15.5 (diff) · 71 actionable findings from 1 signal source. 41 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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100.0% cov · 71 findings

Severity distribution — click a segment to filter

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Severity: Critical 1 High 18 Medium 14 Low 28 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 71 Crowd 0 Layer: Software 3 Frontend 1 Hardware 8 Security 25 Cicd 1 Quality 33

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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.

Duplicates & near-duplicates 5 findings

What it is: Same function copy-pasted into multiple modules with minor variations.

Why it matters: Each copy drifts independently — bug fixes apply to one, miss the others.

How AI causes it: AI completes the same pattern in each file rather than refactoring to a shared helper.

Fix approach: Extract the duplicated logic into the most general module both call sites already import. Add tests at the helper level.

5 matching findings on this repo

low Near-duplicate function bodies in 2 places repo-level
low Near-duplicate function bodies in 4 places repo-level
low Near-duplicate function bodies in 5 places
low Near-duplicate function bodies in 3 places repo-level
low Near-duplicate function bodies in 11 places

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Legacy markers 2 findings

What it is: TODO, FIXME, XXX, HACK comments. Often indicate a known-broken path the author meant to fix.

Why it matters: Each marker is an unfinished thought. Production code shouldn't ship with debt that's documented but not tracked.

How AI causes it: AI mirrors the style of the codebase, so existing TODOs propagate into new code.

Fix approach: Convert each into a ticket. Delete the comment when the ticket lands. Use a pre-commit hook to block new TODOs without an issue link.

2 matching findings on this repo

low Old/deprecated-named symbol `_push_legacy` in server/tests/test_health_engine_l…
low Old/deprecated-named symbol `test_incident_default_trigger_kind_is_legacy` in s…

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Commented-out code 10 findings

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/`.

10 matching findings on this repo

info Commented-code block (6 lines) in frontend/tests/monitors.test.js:98
info Commented-code block (5 lines) in frontend/src/composables/useMonitorTabs.js:3
info Commented-code block (5 lines) in frontend/src/components/monitors/detail/injec…
info Commented-code block (5 lines) in frontend/src/lib/pushNotifications.js:6
info Commented-code block (6 lines) in frontend/src/lib/appVersion.js:3
info Commented-code block (7 lines) in server/whatisup/main.py:247
info Commented-code block (5 lines) in server/whatisup/api/v1/monitors.py:173
info Commented-code block (5 lines) in server/whatisup/models/probe.py:50
info Commented-code block (5 lines) in server/whatisup/models/alert.py:100
info Commented-code block (5 lines) in server/whatisup/services/incident.py:322

View all commented-out code findings →

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