Claude-skill-registry Advanced RE Analysis
Specialized reverse engineering analysis workflows for binary analysis, pattern recognition, and vulnerability assessment
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/advanced-re-analysis" ~/.claude/skills/majiayu000-claude-skill-registry-advanced-re-analysis && rm -rf "$T"
manifest:
skills/data/advanced-re-analysis/SKILL.mdsource content
Advanced Reverse Engineering Analysis Skill
This Skill provides specialized reverse engineering analysis capabilities for binary analysis, pattern recognition, and vulnerability assessment.
Capabilities
Binary Analysis
- Function analysis and classification
- String pattern recognition
- Cross-reference analysis
- Control flow analysis
Pattern Recognition
- Malware pattern detection
- Vulnerability pattern identification
- Security feature analysis
- Code obfuscation detection
Vulnerability Assessment
- Buffer overflow detection
- Format string vulnerability identification
- Integer overflow analysis
- Use-after-free detection
Usage
Basic Analysis
# Analyze binary for security issues analysis_result = analyze_binary_security(binary_data)
Pattern Recognition
# Detect malware patterns malware_indicators = detect_malware_patterns(binary_data)
Vulnerability Assessment
# Assess vulnerabilities vulnerabilities = assess_vulnerabilities(binary_data)
Output Formats
- Technical Reports: Detailed analysis results
- Risk Matrices: Vulnerability risk assessment
- IOC Reports: Indicators of Compromise
- Remediation Guides: Security recommendations
Configuration
Analysis Parameters
: Analysis sensitivity (low, medium, high)sensitivity_level
: Types of patterns to detectpattern_types
: Desired output formatoutput_format
: Include remediation suggestionsinclude_recommendations
Custom Patterns
- Define custom pattern recognition rules
- Configure analysis thresholds
- Set output preferences
Examples
Malware Analysis
# Analyze binary for malware indicators result = analyze_malware_indicators( binary_data=binary_data, sensitivity="high", include_network_indicators=True, include_file_operations=True )
Vulnerability Assessment
# Assess binary for vulnerabilities vulnerabilities = assess_binary_vulnerabilities( binary_data=binary_data, check_buffer_overflows=True, check_format_strings=True, check_integer_overflows=True )
Security Analysis
# Perform comprehensive security analysis security_report = perform_security_analysis( binary_data=binary_data, analysis_depth="comprehensive", include_recommendations=True )
Integration
This Skill integrates with EmberScale to provide:
- Automated Analysis: Automated binary analysis workflows
- Pattern Recognition: Advanced pattern detection capabilities
- Vulnerability Assessment: Comprehensive security assessment
- Report Generation: Automated report generation
- Recommendation Engine: Security improvement suggestions
Requirements
- Binary analysis capabilities
- Pattern recognition algorithms
- Vulnerability detection methods
- Report generation tools
- Security assessment frameworks
Output
The Skill generates comprehensive analysis reports including:
- Executive Summary: High-level findings and recommendations
- Technical Details: Detailed analysis results
- Risk Assessment: Vulnerability risk analysis
- Remediation Guide: Security improvement recommendations
- IOC Report: Indicators of Compromise for threat hunting
Support
For questions and support regarding this Skill:
- Check the documentation
- Review example usage
- Contact the development team
- Submit issues and feedback
Advanced Reverse Engineering Analysis Skill - Specialized binary analysis and security assessment