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yolo-labz/wa

https://github.com/yolo-labz/wa · scanned 2026-06-16 01:07 UTC (2 months, 1 week ago)

14 raw signals (0 security + 14 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 12 actionable findings from 1 signal source. 2 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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88.9% cov · 12 findings

Severity distribution — click a segment to filter

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Severity: Critical 0 High 2 Medium 6 Low 2 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 12 Crowd 0 Layer: Hardware 1 Frontend 1 Security 3 Cicd 1 Quality 6

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 68.3/100 with 88.9% coverage. It contains 960 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 14 findings — concentrated in quality (6), security (3), cicd (3). Risk profile is high: 0 critical, 2 high, 8 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 9 of 12 actionable findings. 14 raw detector signals were grouped into reader-sized issues. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

high System graph security Agent instructions conf 1.00 Agent instruction/config may expose a secret: CLAUDE.md

Agent-facing files are routinely pasted into LLM/tool contexts. Move literal tokens, keys, and passwords into a secret manager or document them as placeholders only.

CLAUDE.md:264 SecretsClaude instruction

high System graph security security conf 1.00 Insecure pattern 'exec_used' in CLAUDE.md:392

Found a known-risky pattern (exec_used). Review and replace if possible.

CLAUDE.md:392 Exec used

medium System graph quality Agent instructions conf 1.00 Agent instructions exist but release-hardening basics are missing

AI-coder instruction files were found, but the repo is missing tests. Treat this as a contract gap: the agent is guided, but the generated output is not yet guarded by the controls that make it repeatable.

Repo hardeningGenerated repo pattern

medium System graph quality Tests conf 1.00 CI is configured but no tests are detected

A CI pipeline exists, but the scan found no test files to gate. Opus labeled this generated-code pattern as config theater: release machinery exists, but it has little behavioral signal.

CI/CDConfig theaterRepo hardening

medium System graph quality Placeholder conf 1.00 Critical user flow still appears backed by mock or placeholder data

A payment/auth/admin/order/billing-style flow contains mock, fake, TODO, dummy, or placeholder markers in runtime source. In the Fable corpus this is a high-leverage completeness smell: the app can look finished while the money, identity, or tenant flow is still scaffolded.

Mock dataCritical flowGenerated repo pattern

medium System graph cicd CI/CD security conf 1.00 3 occurrences GitHub Actions workflow grants broad write permissions

CI tokens with write permissions increase blast radius when an action, dependency, or PR workflow is compromised. Prefer job-level least-privilege permissions.

3 files, 3 locations

.github/workflows/docker-image.yml

.github/workflows/release.yml

.github/workflows/scorecard.yml

CI/CD securitySupply chainGithub actions

medium System graph quality Placeholder conf 1.00 Placeholder or mock-heavy implementation detected

Found 254 placeholder/mock markers across 75 source files. This often means the repo looks complete while core flows still use generated scaffolding or fake data.

Mock dataIncompleteGenerated repo pattern

low System graph hardware Coverage conf 1.00 Containers defined but no K8s/orchestration manifest found

Repo has Dockerfiles/compose but no Kubernetes/Nomad manifests. If the target deployment is K8s, the manifests may live in a separate ops repo.

Deployment

low System graph quality Provenance conf 1.00 Shallow git history limits provenance confidence

The repository is a shallow clone. Origin/evolution analysis cannot distinguish fresh generation, imported legacy code, or long-lived human code with high confidence.

Git historyGenerated repo pattern

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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