Historial de auditorías

Static analysis reported many high-severity weak-cryptography and command-execution patterns, but review found they are false positives in YAML examples, schema documentation, and Markdown code fences. The executable Python script performs intended local repository scanning and metadata generation without subprocess execution or outbound network requests. No prompt injection attempt or malicious intent was found.

All 212 static findings are false positives. The static analyzer misidentifies YAML schema type values (like 'service', 'gateway', 'kafka') as weak cryptographic algorithms and misinterprets markdown backtick formatting as shell command execution. This skill is a legitimate documentation generator that reads local repository files and outputs YAML metadata without network access, credential handling, or code execution beyond Python subprocess calls for git status.

All 212 static findings are false positives. The static analyzer misidentifies YAML schema type values (like 'service', 'gateway', 'kafka') as weak cryptographic algorithms and misinterprets markdown backtick formatting as shell command execution. This skill is a legitimate documentation generator that reads local repository files and outputs YAML metadata without network access, credential handling, or code execution beyond Python subprocess calls for git status.

This is a legitimate documentation generation skill that analyzes repositories to generate service catalog metadata. The Python script reads local files, parses code patterns, and outputs YAML metadata. No network calls, no credential access, no data exfiltration. Standard filesystem operations for documentation purposes.

This is a legitimate documentation generation skill that analyzes repositories to generate service catalog metadata. The Python script reads local files, parses code patterns, and outputs YAML metadata. No network calls, no credential access, no data exfiltration. Standard filesystem operations for documentation purposes.

This is a legitimate documentation generation skill that analyzes repositories to generate service catalog metadata. The Python script reads local files, parses code patterns, and outputs YAML metadata. No network calls, no credential access, no data exfiltration. Standard filesystem operations for documentation purposes.