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sgl-project/sglang

https://github.com/sgl-project/sglang · scanned 2026-06-16 00:11 UTC (2 months, 2 weeks ago) · 10 languages

3566 raw signals (206 security + 3360 graph) 0th percentile · Python · huge (>500K LoC)

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Complete repo analysis

Last scanned 2 months, 2 weeks ago · v2 · last Δ -7.8 (diff) · 1417 actionable findings from 2 signal sources. 1068 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
42.0
/100
Security checks
37
42 findings
System graph
47
100.0% cov · 1375 findings
Critical
6
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Agents
10
0 votes
Crowd
0
reported
Score breakdown â 2026-05-17-v4 calibration-aware
Component Sub-score Weight Contribution
structure_score 40.0 0.15 6.00
security_score 22.9 0.25 5.72
testing_score 100.0 0.20 20.00
documentation_score 66.0 0.15 9.90
practices_score 65.0 0.15 9.75
code_quality 46.9 0.10 4.69
Overall 1.00 56.1
Calibrated penalty buckets (security_score): agent: 3.2 · authz: 1.2 · docker: 50.6 · threat: 45.4 · journey: 2.5
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 6 High 127 Medium 127 Low 660 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 42 System graph 1375 Crowd 0 Layer: Quality 1175 Security 132 Cicd 17 Software 25 Frontend 3 Network 2 Hardware 7 Api 56

Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Duplicates & near-duplicates 3 findings
What it is: Same function copy-pasted into multiple modules with minor variations.
Why it matters: Each copy drifts independently — bug fixes apply to one, miss the others.
How AI causes it: AI completes the same pattern in each file rather than refactoring to a shared helper.
Fix approach: Extract the duplicated logic into the most general module both call sites already import. Add tests at the helper level.
3 matching findings on this repo
  • low Near-duplicate function bodies in 2 places repo-level
  • low Near-duplicate function bodies in 3 places repo-level
  • low Near-duplicate function bodies in 4 places
View all duplicates & near-duplicates findings →
Legacy markers 5 findings
What it is: TODO, FIXME, XXX, HACK comments. Often indicate a known-broken path the author meant to fix.
Why it matters: Each marker is an unfinished thought. Production code shouldn't ship with debt that's documented but not tracked.
How AI causes it: AI mirrors the style of the codebase, so existing TODOs propagate into new code.
Fix approach: Convert each into a ticket. Delete the comment when the ticket lands. Use a pre-commit hook to block new TODOs without an issue link.
5 matching findings on this repo
  • low Old/deprecated-named symbol `test_legacy_checksums_format_deprecated` in test/r…
  • low Old/deprecated-named symbol `generate_legacy` in test/registered/jit/deepseek_v…
  • low Old/deprecated-named symbol `test_gemm_bit_exact_vs_legacy` in test/registered/…
  • low Old/deprecated-named symbol `generate_legacy` in python/sglang/jit_kernel/tests…
  • low Old/deprecated-named symbol `test_explicit_mode_overrides_explicit_legacy` in p…
View all legacy markers findings →
Commented-out code 488 findings
What it is: Lines of source that were intentionally disabled but never deleted.
Why it matters: Git already remembers history — commented code rots, becomes wrong, and adds noise to diffs.
How AI causes it: AI sometimes comments out broken code instead of fixing it. Reviewers approve out of inertia.
Fix approach: Delete. Trust `git log`. If you really need to remember, save it in a notes file under `docs/`.
12 matching findings on this repo
  • info Commented-code block (24 lines) in docs_new/src/snippets/_deployment.jsx:6
  • info Commented-code block (12 lines) in docs_new/src/snippets/_playground.jsx:6
  • info Commented-code block (6 lines) in docs_new/src/snippets/autoregressive/qwen35-d…
  • info Commented-code block (8 lines) in docs_new/src/snippets/autoregressive/kimi-k25…
  • info Commented-code block (6 lines) in docs_new/src/snippets/autoregressive/hunyuan3…
  • info Commented-code block (11 lines) in docs_new/src/snippets/autoregressive/mimo-v2…
  • info Commented-code block (6 lines) in docs_new/src/snippets/autoregressive/laguna-x…
  • info Commented-code block (7 lines) in docs_new/src/snippets/autoregressive/minicpm-…
  • info Commented-code block (6 lines) in docs_new/src/snippets/configs/LiquidAI/lfm2.5…
  • info Commented-code block (5 lines) in docs_new/src/snippets/configs/LiquidAI/lfm2.5…
  • info Commented-code block (9 lines) in docs_new/src/snippets/configs/MiniMaxAI/minim…
  • info Commented-code block (13 lines) in docs_new/src/snippets/configs/MiniMaxAI/mini…
View all commented-out code findings →
Config drift 87 findings
What it is: Settings duplicated across env files, Docker compose, K8s, and code defaults, all with slightly different values.
Why it matters: Production behaviour depends on whichever copy your loader reads first. Subtle bugs in staging that don't reproduce in dev.
How AI causes it: AI writes new config from memory rather than reading the existing source.
Fix approach: Pick one source of truth (env vars + a settings module). Have every other place import from there. Lint for duplicates in CI.
12 matching findings on this repo
  • info TODO/FIXME marker in shipping code — docs_new/src/snippets/configs/MiniMaxAI/mi…
  • low Very large file: python/sglang/multimodal_gen/test/unit/sana_wm/test_pipeline_c…
  • low Very large file: python/sglang/srt/configs/model_config.py (1818 lines)
  • medium Runtime service client appears to use placeholder configuration
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
  • high Agent instruction/config may expose a secret: .claude/skills/llm-serving-auto-b… .claude/skills/llm-serving-auto-benchmark/configs…:8
View all config drift findings →
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