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BaseAI

https://github.com/CommandCodeAI/BaseAI.git · scanned 2026-05-17 01:20 UTC (19 hours, 4 minutes ago) · 10 languages

466 findings (34 legacy + 432 scanner) 18th percentile · Typescript · medium (20-100K LoC) Scanner says 77 (lower by 17)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 19 hours, 4 minutes ago · v3 · 176 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
{# ── 2026-05-17 R27 #5: score breakdown panel ────────────────────── Surfaces the score_breakdown JSON that's been silently stored on Repository for months. Turns hidden math into a trust signal. #}
Score breakdown â 2026-05-17-v4 calibration-aware
Component Sub-score Weight Contribution
structure_score 60.0 0.15 9.00
security_score 100.0 0.25 25.00
testing_score 1.0 0.20 0.20
documentation_score 75.0 0.15 11.25
practices_score 55.0 0.15 8.25
code_quality 60.0 0.10 6.00
Overall 1.00 59.7
Severity distribution — click a segment to filter
Active filters: severity: medium × excluding tests × Reset all
Severity: Critical 0 High 19 Medium 9 Low 125 Source: Legacy 34 9-layer 142 Crowd 0 Layer: Quality 52 Software 53 Frontend 48 Security 2 Cicd 2 Api 19
Scan summary Repository scanned at 77.1/100 with 88.9% coverage. It contains 1612 nodes across 30 cross-layer flows, written primarily in mixed languages. Engine surfaced 142 findings — concentrated in software (50), frontend (48), quality (21). Risk profile is high: 0 critical, 16 high, 8 medium. Recommended next step: open the software layer findings first — that's where the highest-impact wins live.

Showing 9 of 176 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

medium Legacy quality practices No CI/CD configuration found
Add a CI/CD pipeline: create .github/workflows/ci.yml for GitHub Actions with steps to lint, test, and build on every push and pull request.
practiceslegacy
medium 9-layer frontend frontend-quality conf 1.00 `dangerouslySetInnerHTML` used in a React component — apps/baseai.dev/src/components/Code.tsx:389
Open XSS surface unless the input is provably trusted. Replace with explicit JSX or sanitize via a vetted library. Why: OWASP basics. Already partially flagged by the security analyzer. Rule id: fq.dangerous-html
frontend-qualityfq.dangerous-html
medium 9-layer quality integrity conf 1.00 `fetch()` without try/.catch or AbortSignal — packages/baseai/src/add/index.ts:78
Bare `fetch(...)` will throw an unhandled rejection on network failure. Wrap in try/catch, attach a `.catch(...)`, or pass an AbortSignal with a timeout.
integrityfragile-runtimerobustness
medium 9-layer quality integrity conf 1.00 `fetch()` without try/.catch or AbortSignal — packages/baseai/src/deploy/index.ts:286
Bare `fetch(...)` will throw an unhandled rejection on network failure. Wrap in try/catch, attach a `.catch(...)`, or pass an AbortSignal with a timeout.
integrityfragile-runtimerobustness
medium 9-layer quality integrity conf 1.00 `fetch()` without try/.catch or AbortSignal — packages/core/src/react/use-pipe.ts:179
Bare `fetch(...)` will throw an unhandled rejection on network failure. Wrap in try/catch, attach a `.catch(...)`, or pass an AbortSignal with a timeout.
integrityfragile-runtimerobustness
medium 9-layer security owasp conf 1.00 Insecure pattern 'dangerous_innerhtml' in apps/baseai.dev/src/components/Code.tsx:389
Found a known-risky pattern (dangerous_innerhtml). Review and replace if possible.
apps/baseai.dev/src/components/Code.tsx:389 owaspdangerous_innerhtml
medium 9-layer security coverage conf 1.00 No auth library detected
The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). Either auth lives in custom code, in a separate service, or is missing.
coverageauth
medium 9-layer cicd coverage conf 1.00 No CI/CD pipelines detected
No GitHub Actions, GitLab CI, or CircleCI configs found. Without CI you can't gate deploys on tests/lints.
coverage
medium 9-layer quality tests conf 1.00 Very low test-to-source ratio
5 test file(s) for 478 source file(s) (ratio 0.01). Consider adding integration or unit tests for critical paths.
testscoverage
{# ── 2026-05-17 Round 14: AI-agent bridge footer ────────────────────── Discoverability: the /agents/voting/ guide + MCP manifest exist but aren't linked from anywhere users actually land. Small, opt-in footer. #}
For AI agents: Voting guide (TP/FP) MCP manifest Stdio wrapper SARIF Integrate Findings queue Vote TP/FP on findings to calibrate the engine.
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