SkillTotal

Is lightgbm safe?

No malicious indicators - review capabilities before installing
Notable — review in context (capabilities are not malware):
  • Python filesystem read
  • Python filesystem write/delete

What to do: Nothing here argues against installing it. Grant the capabilities it lists only if you expect the tool to need them.

lightgbm is a PyPI package analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators. It can: filesystem read and filesystem write — capabilities are what the code can do, not a verdict on intent. Risk score 0/100 (low).

lightgbm 4.7.0

python_package · pypi:lightgbm
LOW
0
/ 100 risk score
Snapshot · scanned Oct 8, 2026 · lightgbm@4.7.0 · engine 0.56.4 / ruleset 62

Automated static-analysis result. It can contain false positives and false negatives, and is not a claim about the intent of lightgbm's authors. Report a false positive.

Capabilities — what this component can do (not a risk score):
filesystem readfilesystem write

Behavioral traits

How this component maps to the CSA agentic threat model. Descriptive — it never affects the risk score.

Filesystem reach
Tool Execution Context

Findings (2)

MEDIUMPython filesystem readST-FS-PY-READ

The component reads files from disk.

__version__ = _version_path.read_text(encoding="utf-8").strip()
with open(file_name, "rb") as f:
with open(model_file, "r") as file:

Why it matters: Usually legitimate, but worth confirming it can't be steered into reading sensitive files.

Fix: Confirm which files are read and that paths cannot be influenced by untrusted input to reach sensitive locations.

MEDIUMPython filesystem write/deleteST-FS-PY-WRITE

The component writes or deletes files on disk.

with open(file_name, "a") as f:
with open(filename, "w") as file:

Why it matters: Usually legitimate, but worth confirming the paths can't be controlled by untrusted input.

Fix: Confirm which files are written/deleted and that paths cannot be influenced by untrusted input.

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How we determine this: deterministic static analysis (regex + AST), evidence-anchored, no code execution. Methodology →