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shockk73/marix

https://github.com/shockk73/marix · scanned 2026-06-16 00:11 UTC (2 months, 2 weeks ago)

22 raw signals (0 security + 22 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 2 weeks ago · v1 · 21 actionable findings from 1 signal source. 1 repeated signal grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
89.7
/100
Security checks
90
0 findings
System graph
90
100.0% cov · 21 findings
Critical
0
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Agents
10
0 votes
Crowd
0
reported
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 0 High 0 Medium 6 Low 11 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 21 Crowd 0 Layer: Software 1 Api 1 Data 1 Hardware 3 Frontend 1 Security 1 Cicd 1 Quality 12
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Scan summary Repository scanned at 89.7/100 with 100.0% coverage. It contains 634 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 22 findings — concentrated in quality (13), hardware (3), software (1). Risk profile is low: 0 critical, 0 high, 6 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 17 of 21 actionable findings. 22 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.

medium System graph quality Production readiness conf 1.00 Composite production-readiness gap
Multiple low-cost hardening controls are missing together: license, ci, operator-readme. 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 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 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 security Coverage conf 1.00 No auth library detected
The scanner did not find any standard auth library (JWT, OAuth, NextAuth, Auth0, etc.). The repo has auth/admin/session surface indicators, so auth may live in custom code, in a separate service, or be missing.
auth
medium System graph cicd CI/CD security 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.
CI/CD securityCoverage
medium System graph data Coverage conf 1.00 ORM models found but no DB engine detected
The repo defines tables/models but no DB connection string was found. Likely lives in env vars or a config file the scanner didn't read.
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 hardware Supply chain conf 1.00 Docker base image is tag-pinned but not digest-pinned: python:3.12-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 2 occurrences Near-duplicate function bodies in 2 places
Functions with the same first-5-line body hash: providers/baranovichi_session.py:book_trip, providers/baranovichi_session.py:book 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.
2 occurrences
repo-level (2 hits)
duplicatesduplication
low System graph quality Integrity conf 1.00 Near-duplicate function bodies in 4 places
Functions with the same first-5-line body hash: providers/atlasbus.py:get_trips, providers/buspro.py:get_trips, providers/timetable_base.py:get_trips, providers/baranovichi_express.py:get_trips This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.hn/ai-code…
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
low System graph quality Docs conf 1.00 No README detected
No README file was found. Generated repos without README context are hard to operate, validate, or safely hand off.
ReadmeRepo hardeningGenerated repo pattern
low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `canceled_old` in booking_flow.py:166
Names with suffixes like `_old`, `_v1`, `_deprecated` usually indicate replaced-but-not-removed code (typical AI-coder leftover). Confirm and delete, or rename if it's the active version.
old markerDead code
low System graph quality Integrity conf 1.00 Old/deprecated-named symbol `test_execute_rebooking_cancels_old` in tests/test_autobook_flow.py:402
Names with suffixes like `_old`, `_v1`, `_deprecated` usually indicate replaced-but-not-removed code (typical AI-coder leftover). Confirm and delete, or rename if it's the active version.
old markerDead code
low System graph software Dead code conf 1.00 Possibly dead Python function: reset_llm_sessions
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
db.py:782
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
low System graph quality Complexity conf 1.00 Very large file: llm/tools.py (1270 lines)
Files with >800 lines often hide complexity hotspots and discourage tests.
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