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BigBodyCobain/Shadowbroker

https://github.com/BigBodyCobain/Shadowbroker · scanned 2026-06-17 01:23 UTC (1 month, 2 weeks ago)

406 raw signals (0 security + 406 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 month, 2 weeks ago · v2 · last Δ -24.3 (diff) · 379 actionable findings from 1 signal source. 27 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 · 379 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 1 High 46 Medium 50 Low 186 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 379 Crowd 0 Layer: Software 22 Frontend 36 Hardware 5 Security 53 Cicd 3 Quality 208 Api 52

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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 2 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.

2 matching findings on this repo

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

View all duplicates & near-duplicates findings →

Legacy markers 23 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.

12 matching findings on this repo

low Old/deprecated-named symbol `collect_legacy` in backend/main.py:7853
low Old/deprecated-named symbol `collect_legacy` in backend/tests/mesh/test_dm_poll…
low Old/deprecated-named symbol `test_public_ledger_is_union_of_active_and_legacy` …
low Old/deprecated-named symbol `__test_s13d_legacy` in backend/tests/mesh/test_s13…
low Old/deprecated-named symbol `count_legacy` in backend/tests/mesh/test_compatibi…
low Old/deprecated-named symbol `count_legacy` in backend/tests/mesh/test_mesh_dm_s…
low Old/deprecated-named symbol `count_legacy` in backend/tests/mesh/test_s16a_dm_c…
low Old/deprecated-named symbol `count_legacy` in backend/tests/mesh/test_private_m…
low Old/deprecated-named symbol `__test_legacy` in backend/tests/mesh/test_s13c_gat…
low Old/deprecated-named symbol `normalize_dm_message_payload_legacy` in backend/te…
low Old/deprecated-named symbol `dm_test_legacy` in backend/tests/mesh/test_mesh_wo…
low Old/deprecated-named symbol `peer_sender_legacy` in backend/tests/mesh/test_dm_…

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Commented-out code 68 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/`.

12 matching findings on this repo

info Commented-code block (8 lines) in backend/ais_proxy.js:8
info Commented-code block (10 lines) in backend/main.py:1102
info Commented-code block (5 lines) in backend/auth.py:255
info Commented-code block (7 lines) in backend/tests/test_sentinel_routes_auth_gate.…
info Commented-code block (5 lines) in backend/scripts/convert_power_plants.py:23
info Commented-code block (6 lines) in backend/routers/data.py:110
info Commented-code block (5 lines) in backend/routers/health.py:63
info Commented-code block (5 lines) in backend/routers/ai_intel.py:2609
info Commented-code block (5 lines) in backend/routers/tools.py:121
info Commented-code block (5 lines) in backend/routers/wormhole.py:163
info Commented-code block (5 lines) in backend/routers/radio.py:24
info Commented-code block (8 lines) in backend/services/region_dossier.py:22

View all commented-out code findings →

Config drift 4 findings

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.

4 matching findings on this repo

medium Runtime service client appears to use placeholder configuration
info Commented-code block (5 lines) in backend/services/config.py:78
info Commented-code block (7 lines) in frontend/vitest.config.js:11
info Commented-code block (5 lines) in frontend/next.config.ts:10

View all config drift findings →

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