Component Discovery and Identification

The foundation of any SCA tool lies in its ability to accurately discover and identify all components within an application. This process begins with manifest file parsing, where tools analyze package management files like package.json, pom.xml, Gemfile, requirements.txt, or go.mod. These files explicitly declare direct dependencies, providing the starting point for analysis. However, manifest parsing alone provides incomplete visibility, as it misses transitive dependencies, binary inclusions, and components added through non-standard mechanisms.

Advanced discovery techniques extend beyond manifest files to achieve comprehensive coverage. Binary analysis examines compiled code and executables to identify embedded libraries through various fingerprinting methods. Hash-based matching compares file hashes against databases of known components. Signature scanning looks for unique code patterns, strings, or metadata that identify specific libraries. Some tools employ machine learning models trained on millions of components to identify libraries even when modified or obfuscated.

File system scanning represents another crucial discovery method. SCA tools traverse project directories looking for component indicators: JAR files in Java projects, node_modules directories in JavaScript applications, or vendor folders in Go projects. They analyze archive files (ZIP, TAR, JAR) to discover nested components. Container image scanning has become essential, requiring tools to unpack image layers and analyze both OS packages and application-level dependencies. Each discovery method contributes to building a complete component inventory.