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janoskonig/maxillofacialisrehabilitacio

https://github.com/janoskonig/maxillofacialisrehabilitacio · scanned 2026-06-16 04:28 UTC (2 months ago)

12 raw signals (0 security + 12 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months ago · v1 · 12 actionable findings from 1 signal source. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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77.8% cov · 12 findings

Severity distribution — click a segment to filter

Active filters: excluding tests × Reset all

Severity: Critical 0 High 1 Medium 5 Low 5 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 12 Crowd 0 Layer: Frontend 2 Hardware 2 Quality 7 Security 1

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 67.4/100 with 77.8% coverage. It contains 45 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 12 findings — concentrated in quality (7), frontend (2), hardware (2). Risk profile is high: 0 critical, 1 high, 5 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 11 of 12 actionable findings. 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: AGENTS.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.

AGENTS.md:39 SecretsAgents md

medium System graph quality Agent instructions conf 1.00 Agent authority lacks a verifier contract: CLAUDE.md

This agent instruction grants code or shell authority but does not state the verification gate that decides promotion. The recurring safe pattern is: LLM proposes; deterministic tests/build/security checks verify; only verified code promotes.

CLAUDE.md VerificationClaude instruction

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 license, ci, 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 Production readiness conf 1.00 Composite production-readiness gap

Multiple low-cost hardening controls are missing together: license, ci, tests. Opus verification showed these co-occurring gaps are a better readiness signal than reading each flag in isolation.

Repo hardeningGenerated repo pattern

medium System graph hardware Security conf 1.00 Dockerfile runs as root: Dockerfile

No non-root USER set. Containers running as root expand the blast radius of any vulnerability inside the image.

Container

medium System graph quality Tests conf 1.00 Very low test-to-source ratio

1 test file(s) for 11 source file(s) (ratio 0.09). Consider adding integration or unit tests for critical paths.

Coverage

low System graph quality Integrity conf 1.00 13 env vars used in code but missing from .env.example

Drift between code and config docs. The first few: `ANALYZE`, `ENABLE_SENTRY`, `HOSTNAME`, `JWT_SECRET`, `NEXT_PUBLIC_ENABLE_SENTRY`, `NEXT_PUBLIC_SENTRY_DSN`, `NEXT_PUBLIC_SENTRY_RELEASE`, `PORT` + 5 more. Add them (with a placeholder/comment) to .env.example so onboarding doesn't break.

config drift

low System graph hardware Supply chain conf 1.00 Docker base image is tag-pinned but not digest-pinned: node:20-slim

Container tags can be retagged upstream. Pin production base images to a reviewed digest (`image@sha256:...`) when reproducibility and supply-chain integrity matter.

Dockerfile:2 containersPinned dependencies

low System graph quality Agent instructions conf 1.00 Multiple root agent instruction files without precedence

The repo has multiple top-level AI-coder instruction files. Without precedence rules, different agents may follow different policies.

Governance

low System graph quality License conf 1.00 No license file detected

No LICENSE/COPYING/NOTICE file was found. Generated repositories often omit licensing, which blocks reuse and automated intake.

Repo hardeningGenerated repo pattern

low System graph frontend Frontend quality conf 1.00 Stray `console.log` in TS/JS — server.ts:49

Replace with the toast helper, an error boundary, or remove. `console.warn` / `console.error` are acceptable. Why: Hygiene — easy to leak debug output. Rule id: fq.console-leak

Fq console leak

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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