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114 of your 186 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.
Upstream (GitHub) caused delay on this scan — not Repobility.
  • GitHub API rate-limited (HTTP 403) — preflight skipped, fell back to direct git clone.
  • Clone from GitHub took 55.9s for a 126.4 MB repo slow.
  • Repobility's analysis ran in 8.43s after the clone landed.

unilabsim/UniLab

https://github.com/unilabsim/UniLab · scanned 2026-06-05 14:33 UTC (5 days, 4 hours ago) · 10 languages

423 raw signals (173 security + 250 graph) 11/13 scanners ran 96th percentile · Python · large (100-500K LoC) System graph score 79 (higher by 12)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 5 days, 4 hours ago · v2 · 162 actionable findings from 2 signal sources. 111 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
85.6
/100
Security checks
92
60 findings
System graph
79
88.9% cov · 102 findings
Critical
2
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 85.0 0.15 12.75
security_score 100.0 0.25 25.00
testing_score 100.0 0.20 20.00
documentation_score 100.0 0.15 15.00
practices_score 90.0 0.15 13.50
code_quality 45.0 0.10 4.50
Overall 1.00 90.8
security_score may be inflated — optional security scanners were skipped on this fast scan
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 2 High 36 Medium 11 Low 65 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 60 System graph 102 Crowd 0 Layer: Quality 89 Cicd 6 Software 29 Security 32 Api 1 Hardware 4 Frontend 1

Top 10 actions, ranked by impact × ease. Severity drives impact; tag-based fix-clarity drives ease.

#1
Insecure pattern 'eval_used' in scripts/train_hora_distill.py:272
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
scripts/train_hora_distill.py:272
#2
Insecure pattern 'eval_used' in scripts/train_offpolicy.py:428
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
scripts/train_offpolicy.py:428
#3
Insecure pattern 'eval_used' in scripts/train_appo.py:231
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
scripts/train_appo.py:231
#4
Insecure pattern 'eval_used' in scripts/train_mlx_ppo.py:267
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
scripts/train_mlx_ppo.py:267
#5
Insecure pattern 'eval_used' in benchmark/benchmark_mlp_inference.py:362
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
benchmark/benchmark_mlp_inference.py:362
#6
Insecure pattern 'eval_used' in benchmark/benchmark_backends.py:174
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
benchmark/benchmark_backends.py:174
#7
Insecure pattern 'eval_used' in benchmark/benchmark_conversions.py:142
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
benchmark/benchmark_conversions.py:142
#8
Insecure pattern 'eval_used' in benchmark/benchmark_ane_inference.py:96
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
benchmark/benchmark_ane_inference.py:96
#9
Insecure pattern 'eval_used' in benchmark/benchmark_ane_peak.py:77
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
benchmark/benchmark_ane_peak.py:77
#10
Insecure pattern 'eval_used' in benchmark/benchmark_ipc_weight_sync.py:177
GapSeverity.HIGH Layer.SECURITY score 0.413
Why: high severity · OWASP-class risk
benchmark/benchmark_ipc_weight_sync.py:177

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