Versioned security assessment

Report ID: SA-A74231AC

6/30/2026, 5:50:12 AM

statistical-analysis security assessment v5

Skill Security Certification Report

Audit History
Audit model: codex Historical report
Skill name
statistical-analysis
Version
v5
Maintainer
K-Dense-AI
Source
github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/statistical-analysis
Coverage
7 Files scanned · 3,386 Lines analyzed
Policy version
Unavailable

Highest confirmed finding severity

Low

1 confirmed security finding requires attention.

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.

The static analyzer reported many high-risk patterns, but review found these are false positives from Markdown code fences, statistical notation, and documentation links. The only real risk factor is a local Python helper script for statistical assumption checks, with no evidence of shell execution, network requests, credential access, file deletion, or prompt injection.

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 · 3,386 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.

Observed in 3 evidence locations

Network access

May connect to external services.

Not recorded by this audit

Filesystem access

May read or write local files.

Not recorded by this audit

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

Risk findings

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

Confirmed security concerns (1)

RISK-001 Low
scripts/assumption_checks.py:12-17scripts/assumption_checks.py:409-417scripts/assumption_checks.py:520-539
Local Statistical Helper Script Requires Normal Script Review
The skill includes a Python helper module for assumption checks using NumPy, pandas, SciPy, matplotlib, and seaborn. It processes local data and plots diagnostics; no evidence found for shell execution, network access, secret access, or destructive file operations.
The script is real executable code, so it is a valid risk factor. Confidence is high that it is low risk because inspected imports and functions are local statistical calculations and plotting.

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:62-79SKILL.md:124-164references/effect_sizes_and_power.md:38-61references/bayesian_statistics.md:33-40
Markdown Code Examples Misclassified as Shell Execution
The external command findings point to Markdown code fences and inline code used for statistical Python examples and decision trees. I found no Ruby backtick execution or shell invocation in these locations.
The cited lines are Markdown fences or Python/statistical examples, not executable Ruby or shell code. The reviewed context shows educational examples rather than command execution.
Low
references/effect_sizes_and_power.md:3-13references/bayesian_statistics.md:30-48references/reporting_standards.md:92-105references/test_selection_guide.md:102-123
Statistical Notation Misclassified as Weak Cryptography
The weak cryptography findings correspond to statistical terms such as alpha levels, p-values, confidence intervals, and Bayesian probability notation. No hashing, encryption, or cryptographic implementation was found in the reviewed evidence.
The cited content discusses statistical methodology and reporting conventions. There is no semantic evidence of weak cryptographic algorithms or security-sensitive cryptography.
Low
SKILL.md:627-628references/reporting_standards.md:431-438
Documentation URLs Misclassified as Network Behavior
The network findings are static URLs in reference text, including an APA style resource and an example OSF data availability statement. These Markdown links do not perform outbound requests.
The evidence is documentation-only Markdown text. Repository search found no requests, urllib, sockets, curl, wget, or similar network execution code.

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