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vuoalbert/polymarket-bot

https://github.com/vuoalbert/polymarket-bot · scanned 2026-06-16 00:53 UTC (2 months, 1 week ago)

41 raw signals (0 security + 41 graph)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 months, 1 week ago · v1 · 25 actionable findings from 1 signal source. 16 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
85.5
/100
Security checks
86
0 findings
System graph
86
77.8% cov · 25 findings
Critical
0
click to filter
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 10 Low 11 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 25 Crowd 0 Layer: Software 1 Hardware 7 Frontend 1 Security 2 Cicd 1 Quality 13
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Scan summary Repository scanned at 85.5/100 with 77.8% coverage. It contains 369 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 41 findings — concentrated in quality (24), hardware (9), software (4). Risk profile is low: 0 critical, 0 high, 10 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 21 of 25 actionable findings. 41 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 hardware Supply chain conf 1.00 Docker base image uses a mutable or implicit tag: polymarket-recorder:latest
Container tags can be retagged upstream. Pin production base images to a reviewed digest (`image@sha256:...`) when reproducibility and supply-chain integrity matter.
research/volmodel/Dockerfile:1 containersPinned dependencies
medium System graph hardware Security conf 1.00 Dockerfile runs as root: engine/neon-img/Dockerfile
No non-root USER set. Containers running as root expand the blast radius of any vulnerability inside the image.
Container
medium System graph hardware Security conf 1.00 Dockerfile runs as root: executor/Dockerfile
No non-root USER set. Containers running as root expand the blast radius of any vulnerability inside the image.
Container
medium System graph hardware Security conf 1.00 Dockerfile runs as root: recorder/Dockerfile
No non-root USER set. Containers running as root expand the blast radius of any vulnerability inside the image.
Container
medium System graph hardware Security conf 1.00 Dockerfile runs as root: research/volmodel/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 security conf 1.00 Insecure pattern 'direct_innerhtml_assignment' in dashboard/generate.py:392
Found a known-risky pattern (direct_innerhtml_assignment). Review and replace if possible.
dashboard/generate.py:392 Direct innerhtml assignment
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 quality Tests conf 1.00 Very low test-to-source ratio
2 test file(s) for 55 source file(s) (ratio 0.04). Consider adding integration or unit tests for critical paths.
Coverage
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 Debug conf 1.00 Debug logging residue appears in source files
Found 349 console/debugger/print-style debug statements in non-test source. This is a common fast-generation residue before production cleanup.
CleanupRepo hardeningGenerated repo pattern
low System graph hardware Supply chain conf 1.00 3 occurrences 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.
3 files, 3 locations
engine/neon-img/Dockerfile:1
executor/Dockerfile:3
recorder/Dockerfile:1
containersPinned dependencies
low System graph quality Integrity conf 1.00 12 occurrences Near-duplicate function bodies in 2 places
Functions with the same first-5-line body hash: recorder/siv_recorder.py:log, recorder/deribit_oi_recorder.py:log 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.
12 occurrences
repo-level (12 hits)
duplicatesduplication
low System graph quality Integrity conf 1.00 Near-duplicate function bodies in 3 places
Functions with the same first-5-line body hash: research/backfill/fetch_updown_history.py:get, research/backfill/fetch_15m.py:get, research/altcoins/fetch_markets_alt.py:get This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.hn/ai-code-hygiene). Consolida…
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: research/backfill/replay_volbet.py:kf, research/backfill/replay_h8.py:kf, research/backfill/replay_bigmove.py:kf, research/backfill/per_coin_b.py:kf_btceth This is *the* AI-coder failure mode (4× more duplication in vibe-coded repos — see https://jw.…
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 Integrity conf 1.00 Old/deprecated-named symbol `maker_replay_v2` in research/backfill/maker_replay_v2.py:20
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 4 occurrences Possibly dead Python function: loss
No callers detected by AST scan in this repo. Could be exported for external callers or a framework handler.
4 files, 4 locations
research/altcoins/fit_altcoins.py:105
research/backfill/replay_h8.py:79
research/volmodel/fit.py:99
research/volmodel/fit_v6.py:158
low System graph quality Docs conf 1.00 README lacks setup or run instructions
A README exists, but it does not contain common install/setup/run markers. This matches a frequent generated-code pattern: UI is present, operational handoff is thin.
ReadmeRepo hardeningGenerated repo pattern
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
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