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axolotl-ai-cloud/axolotl

https://github.com/axolotl-ai-cloud/axolotl · scanned 2026-06-17 01:37 UTC (1 month, 2 weeks ago)

234 raw signals (0 security + 234 graph)

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Complete repo analysis

Last scanned 1 month, 2 weeks ago · v2 · last Δ -5.9 (diff) · 142 actionable findings from 1 signal source. 92 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

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77.8% cov · 142 findings

Severity distribution — click a segment to filter

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Severity: Critical 0 High 19 Medium 13 Low 68 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 0 System graph 142 Crowd 0 Layer: Software 26 Hardware 2 Security 20 Cicd 3 Quality 91

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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 5 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.

5 matching findings on this repo

low Near-duplicate function bodies in 2 places repo-level
low Near-duplicate function bodies in 9 places
low Near-duplicate function bodies in 3 places repo-level
low Near-duplicate function bodies in 10 places
low Near-duplicate function bodies in 4 places

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Legacy markers 4 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.

4 matching findings on this repo

low Old/deprecated-named symbol `tokenizer_legacy` in src/axolotl/utils/schemas/mod…
low Old/deprecated-named symbol `load_legacy` in src/axolotl/integrations/kd/chat_t…
low Old/deprecated-named symbol `_do_merge_lora_legacy` in src/axolotl/cli/merge_lo…
low Old/deprecated-named symbol `tokenizer_legacy` in src/axolotl/loaders/tokenizer…

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Commented-out code 38 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 (5 lines) in tests/conftest.py:225
info Commented-code block (5 lines) in tests/integrations/monkeypatch/test_tiled_mlp…
info Commented-code block (6 lines) in tests/integrations/kernels/scattermoe_lora/te…
info Commented-code block (6 lines) in tests/integrations/kernels/scattermoe_lora/be…
info Commented-code block (6 lines) in tests/monkeypatch/test_trl_vllm.py:276
info Commented-code block (5 lines) in tests/prompt_strategies/test_chat_templates_a…
info Commented-code block (7 lines) in tests/e2e/test_quantization.py:97
info Commented-code block (5 lines) in tests/e2e/test_activation_offloading.py:338
info Commented-code block (5 lines) in src/axolotl/processing_strategies.py:118
info Commented-code block (7 lines) in src/axolotl/scripts/vllm_serve_lora.py:323
info Commented-code block (5 lines) in src/axolotl/utils/model_shard_quant.py:106
info Commented-code block (5 lines) in src/axolotl/utils/config/__init__.py:272

View all commented-out code findings →

Config drift 4 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.

4 matching findings on this repo

high Insecure pattern 'exec_used' in src/axolotl/integrations/config.py:53 src/axolotl/integrations/config.py:53
low Very large file: src/axolotl/utils/schemas/config.py (2043 lines)
low Old/deprecated-named symbol `deepseek_v2` in src/axolotl/utils/schemas/config.p…
info Commented-code block (5 lines) in src/axolotl/utils/config/__init__.py:272

View all config drift findings →

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