Advanced dependency analysis from Enforster AI goes beyond surface-level scanning. Enforster analyzes transitive dependencies, identifies hidden vulnerabilities, and provides comprehensive risk assessment for your entire software supply chain.
Recursive scanning of transitive dependencies and nested components
Machine learning evaluates vulnerability severity and business impact
Complete visibility into your software supply chain and dependencies
Enforster's Deep SCA provides unprecedented visibility into your software supply chain. Our advanced engine goes beyond simple dependency scanning to analyze the complete dependency tree, identify hidden vulnerabilities, assess business impact, and provide actionable remediation guidance.
Recursive scanning of all dependency levels to identify hidden vulnerabilities deep in your dependency tree.
AI-powered risk assessment that considers vulnerability severity, business impact, and exploitability.
Enforster provides complete mapping of your dependency hierarchy with unlimited depth analysis and relationship visualization.
Enforster AI identifies vulnerabilities in transitive dependencies that traditional SCA tools miss.
Evaluates how vulnerabilities affect your business operations and customer data.
Comprehensive monitoring of your software supply chain for potential security risks.
Node.js packages and JavaScript dependencies
Python packages and pip dependencies
Java packages and Maven dependencies
.NET packages and C# dependencies
Ruby packages and gem dependencies
Go packages and module dependencies
Comprehensive scanning of all direct and transitive dependencies across your entire codebase with Enforster AI.
Deep analysis of known vulnerabilities and potential security risks in your dependency tree.
AI-powered risk prioritization based on business impact and exploitability factors.
Actionable recommendations for vulnerability remediation and dependency updates.
Experience the power of deep software composition analysis with Enforster's comprehensive SCA security scanning.