Versioned security assessment

Report ID: SA-D9B9E3A0

6/30/2026, 5:48:09 AM

pyopenms security assessment v5

Skill Security Certification Report

Audit History
Audit model: codex Historical report
Skill name
pyopenms
Version
v5
Maintainer
K-Dense-AI
Source
github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/pyopenms
Coverage
7 Files scanned · 2,816 Lines analyzed
Policy version
Unavailable

Confirmed finding summary

No confirmed security findings

The completed audit recorded no confirmed security findings. This is not proof that the Skill has no side effects.

Installation context

Historical evidence

This report may not describe the currently installable artifact. Open the current Skill page for install guidance.

Open current Skill page

This report does not block or authorize the manifest or ZIP.

Static analysis reported many external command, weak cryptography, sensitive key, and reconnaissance patterns. Manual review found these are false positives from Markdown code fences, scientific terminology, parameter keys, file metadata examples, and documentation URLs. No prompt injection, credential access, exfiltration, or malicious execution intent was found; the remaining real concern is normal local filesystem use for mass spectrometry files.

Report position

Historical report

Open audit history before using this report to install.

Audit attestation

Not attestable

The required immutable binding is incomplete.

Human verification

Not verified

No human verification is recorded for this report.

Coverage

7 Files scanned · 2,816 Lines analyzed

1 item shown for review

Limitations

This report does not claim runtime or sandbox execution and does not prove the absence of side effects.

Evidence chain

Follow the evidence from source binding to the install contract. Available evidence supports verification; it is not a safety guarantee.

  1. Source

    Binding unavailable

  2. Artifact

    Identity incomplete

  3. Audit

    Complete

  4. Install contract

    Open manifest to verify

    Open manifest

Capabilities observed

Observed means this report recorded supporting evidence. Not recorded does not prove that a capability is absent.

Contains scripts

May execute code included with the Skill.

Not recorded by this audit

Network access

May connect to external services.

Not recorded by this audit

Filesystem access

May read or write local files.

Observed in 5 evidence locations

Env variables

May read values from the process environment.

Not recorded by this audit

External commands

May invoke commands or programs outside the Skill.

Not recorded by this audit

Capability review items (1)
Low
SKILL.md:47references/file_io.md:114-127references/metabolomics.md:109-117references/feature_detection.md:241-298
Legitimate local file reads and writes are central to the skill
The skill guides users to load and store mzML, idXML, featureXML, consensusXML, mzTab, CSV, and related files. This is expected for mass spectrometry analysis, but users should verify paths and keep raw files separate from outputs. Verdict: TRUE_POSITIVE as filesystem behavior, but LOW severity due legitimate and user-directed context. Confidence: 0.90. Confidence reasoning: Multiple examples explicitly call pyOpenMS load and store methods on local user-provided scientific files.
Multiple examples explicitly call pyOpenMS load and store methods on local user-provided scientific files.

Risk findings

Confirmed security concerns are separated from items that still need review.

No confirmed security findings were recorded for this completed audit.

Expert evidence

Immutable subject identity, scanner metadata, dismissed matches, and source-level evidence.

Artifact subject

Marketplace commit
Unavailable
Content hash
Unavailable
Tree hash
Unavailable
Skill path
Unavailable
Audit payload hash
Unavailable

Analysis metadata

Audit model: codex

Analysis state: Complete

Scope is limited to the recorded files, lines, methods, and evidence. No runtime or sandbox execution is claimed.

Static false positives ignored (3)
Low
SKILL.md:19-25references/feature_detection.md:22-49references/file_io.md:134-139
Static external command findings are Markdown examples
The reported Ruby or shell backtick execution locations are Markdown fenced code blocks and ordinary Python examples. SKILL.md includes an installation command and Python snippets, while reference files contain pyOpenMS examples. These blocks are instructional text, not hidden executable skill code. Verdict: FALSE_POSITIVE. Confidence: 0.96. Confidence reasoning: The reviewed lines show Markdown fences and Python examples with no dynamic command construction or shell execution path.
The reviewed lines show Markdown fences and Python examples with no dynamic command construction or shell execution path.
Low
SKILL.md:203-205
Hardcoded URLs are documentation references
The network findings in SKILL.md point to pyOpenMS documentation, OpenMS documentation, and the OpenMS GitHub repository. I did not find fetch, curl, webhook, upload, or other code that sends local data to these URLs. Verdict: FALSE_POSITIVE. Confidence: 0.98. Confidence reasoning: The URLs are listed under Resources as human-readable documentation links and are not used by executable code.
The URLs are listed under Resources as human-readable documentation links and are not used by executable code.
Low
SKILL.md:160-168references/data_structures.md:440-448references/metabolomics.md:356-378references/identification.md:231-239
Sensitive key and weak crypto flags are scientific context false positives
The sensitive and weak cryptography detections map to terms such as params.keys(), headers.keys(), file descriptions, protein sequences, FDR, and feature identifiers. These are mass spectrometry data structures and biological analysis examples, not certificate handling, credential access, or cryptographic algorithms. Verdict: FALSE_POSITIVE. Confidence: 0.94. Confidence reasoning: The sampled flagged lines are scientific metadata and Python dictionary or parameter access patterns, with no secret material or crypto API calls.
The sampled flagged lines are scientific metadata and Python dictionary or parameter access patterns, with no secret material or crypto API calls.

Verify and export

JSON report CITATION.cff SARIF 2.1.0 Signed installation manifest

The manifest and lockfile bind install artifacts to cryptographic hashes. This integrity claim is separate from the security assessment.

Audit attestation: not_attestable