Security Audit

dkyazzentwatwa/chatgpt-skills:ab-test-calculator

github.com/dkyazzentwatwa/chatgpt-skills

AI SkillCommit d4bad33523ff

TRUSTED

Scanned about 1 month ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

dkyazzentwatwa/chatgpt-skills:ab-test-calculator received a trust score of 79/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.

SkillShield's automated analysis identified 3 findings: 0 critical, 0 high, 3 medium, and 0 low severity. Key findings include Unpinned Python dependency version, Unpinned or Broadly Pinned Dependencies.

The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.

Last analyzed on February 24, 2026 (commit d4bad335). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

100%

Static Code Analysis

93%

Dependency Graph

86%

LLM Behavioral Safety

100%

Behavioral Risk Signals

Filesystem Write

1 finding

Security Findings3

Severity	Finding	Layer	Location
MEDIUM	Unpinned Python dependency version Requirement 'scipy>=1.10.0' is not pinned to an exact version. Pin Python dependencies with '==<exact version>'.	Dependencies	ab-test-calculator/scripts/requirements.txt:1
MEDIUM	Unpinned Python dependency version Requirement 'numpy>=1.24.0' is not pinned to an exact version. Pin Python dependencies with '==<exact version>'.	Dependencies	ab-test-calculator/scripts/requirements.txt:2
MEDIUM	Unpinned or Broadly Pinned Dependencies The `scripts/requirements.txt` file specifies dependencies with broad version ranges (`>=1.10.0`, `>=1.24.0`) instead of exact versions. This can lead to supply chain risks, as future versions of these packages might introduce breaking changes, vulnerabilities, or even malicious code without explicit review. While `scipy` and `numpy` are generally trusted, relying on broad ranges increases the attack surface. Pin dependencies to exact versions (e.g., `scipy==1.10.0`, `numpy==1.24.0`) to ensure deterministic builds and prevent unexpected changes or vulnerabilities from being introduced through dependency updates. Use a lock file (e.g., `pip freeze > requirements.lock`) or a tool like Poetry/Pipenv for better dependency management.	Static	scripts/requirements.txt:1

Scan History

Embed Code

[![SkillShield](https://skillshield.io/api/v1/badge/f04b26f923c0624e.svg)](https://skillshield.io/report/f04b26f923c0624e)