Audit History

The static analyzer flagged 71 patterns, but review showed they are documentation false positives in Markdown. Python import statements, COBRApy object identifiers, code fences, and a public documentation URL do not execute commands, access secrets, or perform network activity. No semantic prompt injection or data-exfiltration intent was found.

The static analyzer flagged 71 patterns, but review showed they are documentation false positives in Markdown. Python import statements, COBRApy object identifiers, code fences, and a public documentation URL do not execute commands, access secrets, or perform network activity. No semantic prompt injection or data-exfiltration intent was found.

AI review found the critical heuristic to be a false positive caused by Markdown Python examples with imports, model I/O, plotting, and CSV export. The hardcoded URLs point to COBRApy documentation and an optional K-Dense Web suggestion; no credential access, network execution, or prompt injection evidence was found. Risk is low because users may copy examples that read or write local scientific files.

All 160 static findings are FALSE POSITIVES. The skill consists only of markdown documentation files containing Python code examples for the COBRApy metabolic modeling library. The scanner misidentified Python parenthesized imports as dynamic import() expressions, markdown backticks as shell command execution, metabolic modeling terminology (blocked reactions, essential genes) as system reconnaissance, and .get_by_id() method calls as credential access patterns. No executable code, network requests, credential handling, or malicious behavior present.

All 160 static findings are FALSE POSITIVES. The skill consists only of markdown documentation files containing Python code examples for the COBRApy metabolic modeling library. The scanner misidentified Python parenthesized imports as dynamic import() expressions, markdown backticks as shell command execution, metabolic modeling terminology (blocked reactions, essential genes) as system reconnaissance, and .get_by_id() method calls as credential access patterns. No executable code, network requests, credential handling, or malicious behavior present.

All 152 static findings are FALSE POSITIVES. The skill consists only of markdown documentation files with Python code examples for the COBRApy metabolic modeling library. The 'backtick execution' flags triggered on Python docstrings in code blocks. 'Weak crypto' flags triggered on scientific terms. 'System reconnaissance' flags triggered on metabolic modeling terminology like 'blocked reactions' and 'essential genes'. 'Credential access' flags triggered on model attribute references (model.reactions). No executable code, network requests, or credential handling found.

Documentation-only skill containing markdown files with COBRApy workflow examples. No executable code, network calls, file system access, or external commands present. Pure instructional content for metabolic modeling.