Which of the following is a key benefit of using a software composition analysis (SCA) tool in a cloud application security program?
Software composition analysis inventories third-party and open-source dependencies, then matches their versions against vulnerability databases to flag known CVEs. This directly satisfies the stem's requirement by identifying inherited risk in libraries the development team did not author, which static code analysis of first-party code alone would miss.
Why this answer
SCA tools automate the identification of open-source components within a codebase and cross-reference them against databases like the National Vulnerability Database (NVD) to detect known vulnerabilities (CVEs). This is a key benefit because cloud applications often heavily rely on open-source libraries, and SCA provides a scalable way to manage that risk without manual auditing.
Exam trap
ISC2 often tests the distinction between SCA (open-source dependency scanning) and SAST (proprietary code scanning), so the trap here is confusing which tool analyzes which type of code, leading candidates to incorrectly select option D.
How to eliminate wrong answers
Option B is wrong because enforcing runtime policies is the function of a Runtime Application Self-Protection (RASP) tool or a cloud workload protection platform (CWPP), not an SCA tool which focuses on static analysis of dependencies. Option C is wrong because simulating attacks on running applications is the purpose of a dynamic application security testing (DAST) tool or a penetration testing framework, not SCA which does not execute code. Option D is wrong because identifying vulnerabilities in proprietary code is the domain of static application security testing (SAST) tools that analyze custom source code, whereas SCA specifically targets open-source and third-party components.