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JKHeadley/instar

https://github.com/JKHeadley/instar · scanned 2026-05-15 20:53 UTC (2 weeks, 6 days ago) · 10 languages

779 findings (209 legacy + 570 scanner) 10th percentile · Typescript · huge (>500K LoC) Scanner says 70 (higher by 2)

File as issue Image v2 schema
UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 weeks, 6 days ago · v1 · 199 findings from 1 source. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

JSON
Combined
70.8
/100
Repobility
72
199 legacy
9-layer
70
100.0% cov · 0 gaps
Critical
14
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-17-v4 calibration-aware
Component Sub-score Weight Contribution
structure_score 85.0 0.15 12.75
security_score 58.4 0.25 14.60
testing_score 95.0 0.20 19.00
documentation_score 69.6 0.15 10.44
practices_score 65.0 0.15 9.75
code_quality 54.8 0.10 5.48
Overall 1.00 72.0
Calibrated penalty buckets (security_score): web: 1.6 · agent: 3.2 · authz: 39.8 · docker: 1.2 · threat: 10.3 · journey: 5.4
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 14 High 150 Medium 9 Low 25 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 199 9-layer 0 Crowd 0 Layer: Quality 56 Software 8 Security 133 Cicd 2

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 56 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 Magic number used as default arg tests/e2e/file-viewer-e2e.test.ts:108
  • medium Magic number used as default arg tests/e2e/scope-coherence-lifecycle.test.ts:169
  • medium Magic number used as default arg tests/unit/activity-partitioner.test.ts:305
  • medium Magic number used as default arg tests/unit/InboundMessageGate.test.ts:66
  • medium Magic number used as default arg tests/unit/nonce-store-config.test.ts:49
  • medium Magic number used as default arg tests/unit/nonce-store-config.test.ts:42
  • medium Magic number used as default arg tests/unit/branch-manager.test.ts:91
  • medium Magic number used as default arg tests/unit/branch-manager.test.ts:81
  • medium Magic number used as default arg tests/unit/middleware-behavioral.test.ts:208
  • medium Magic number used as default arg tests/unit/CommitmentTracker.test.ts:865
  • medium Magic number used as default arg tests/unit/request-timeout.test.ts:43
  • medium Magic number used as default arg tests/unit/agent-bus-replay-protection.test.ts:707
View all fragile runtime findings →
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 CORS misconfiguration — wildcard Access-Control-Allow-Origin tests/unit/middleware-behavioral.test.ts:16
View all config drift findings →
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