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tutoria-chat/tutoria-worker

https://github.com/tutoria-chat/tutoria-worker · scanned 2026-06-16 04:40 UTC (1 month, 3 weeks ago)

5 raw signals (0 security + 5 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 month, 3 weeks ago · v1 · 5 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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66.7% cov · 5 findings

Severity distribution — click a segment to filter

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Severity: Critical 0 High 0 Medium 1 Low 4 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 5 Crowd 0 Layer: Hardware 2 Quality 3

Exclude dismissed / FP Exclude test files

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Scan summary Repository scanned at 89.6/100 with 66.7% coverage. It contains 18 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 5 findings — concentrated in quality (3), hardware (2). Risk profile is low: 0 critical, 0 high, 1 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 5 of 5 actionable findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

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

low System graph quality Production readiness conf 1.00 Composite production-readiness gap

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

Repo hardeningGenerated repo pattern

low System graph hardware Supply chain conf 1.00 Docker base image is tag-pinned but not digest-pinned: python:3.13-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:1 containersPinned dependencies

low System graph quality Integrity conf 1.00 Near-duplicate function bodies in 2 places

Functions with the same first-5-line body hash: run.py:run_dev, run.py:run_prod This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.hn/ai-code-hygiene). Consolidate or document why they're separate.

duplicatesduplication

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

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