Today’s containerized, cloud-native, and DevOps environments rely upon software built from many components. According to analysis published in the 2023 Open Source Report, up to 96% of commercial applications contain open-source code. The “shift left” movement espouses earlier and continuous software testing, enabling developers and security teams to move faster without neglecting security and quality. Managing the potential vulnerabilities from open-source software development, including security, license compliance, and code quality risks, requires Software Composition Analysis (SCA) tools.
As a type of Application Security Testing (AST), SCA provides automated and deep analysis of open-source packages used within an application. When deployed throughout the development process, SCA analyzes dependencies to determine if they harbor any known vulnerabilities. Leveraging Software Composition Analysis helps developers and other stakeholders manage risk exposure that may lurk in open-source code.
What is Software Composition Analysis (SCA)?
Software Composition Analysis helps teams manage their open-source components, automating and performing configuration assessments of IT assets while tracking compliance status based on hardening benchmarks from the Center for Internet Security (CIS).
How Does Software Composition Analysis (SCA) Work?
SCA tools discover related components, their supporting libraries, and any direct and indirect dependencies like software licenses and vulnerabilities that may create potential exploits.
SCA includes analysis of the software data, including:
- source code
- binary files
- container images
- manifest files
- package managers
Any open-source code identified through this analysis is compiled into a Bill of Materials (BOM) and compared against publicly-available or private databases that include known and common vulnerabilities. A U.S. government repository, the National Vulnerability Database (NVD)
In addition to vulnerability reviews, the BOM can be compared against commercial databases to reveal any licenses associated with the code. Lastly, the SCA tool reviews code quality, including version control and contribution history. These comparisons uncover critical security, code quality, as well as legal vulnerabilities that must be mitigated quickly.
SCA Delivers Security, Speed, and Reliability
DevOps teams can no longer track open-source code bases manually. Nor can they follow the increasing complexity of modern applications, particularly at the pace and rigor needed for cloud-native applications.
SCA takes the burden off of teams by fettering out the critical vulnerability in software found in dependencies…or dependencies on top of dependencies. In today’s infrastructure as code (IaC) and Kubernetes environments, SCA supports development velocity where software is built upon layers and containers.
Using SCA improves the software’s configuration posture in accordance with CIS benchmarks but also compares that composition against Industry standards, including PCI-DSS, HIPAA, and NIST.
What Software Composition Analysis (SCA) Tool Features are Most Important?
Knowledge bases: One of the most important aspects of any Software Composition Analysis tool is its knowledge base that compares current software dependencies and codebases. Any solution should quantify and possibly outline their databases of open-source licenses, unique vulnerabilities, and projects. An SCA tools’ repository should include NVD but could also go beyond publicly-available open-source, license, and security information.
Single or multi-factor scanning: Extending past scanning a singular dependency, SCA tools deliver more value when they offer multi-factor scanning, including binary, dependency, and signature scanning.
Prioritized vulnerabilities: Some SCA solutions offer curated and prioritized security notifications with alerts that could be three weeks earlier than what’s included in the government’s vulnerability database. Faster and more detailed vulnerability descriptions and severity scoring can expedite remediation.
Integrating across CI/CD workflows: SCA tools work best when seamlessly integrated into existing DevOps operations and CI/CD workflows. IDE integration is also desirable where developers see real-time issues and can circumvent new vulnerabilities during earlier SDLC stages.
Software BOM: SCA tools should be able to create a software BOM, including open-source details and dependencies like versioning, known vulnerabilities, and licenses for every component.
How is SCA Different from SAST?
Software composition analysis or SCA reviews open-source and third-party components rather than just scanning internally-developed code. While SAST and SCA are the most popular application security testing tools, they have distinctions that may indicate one is more appropriate or should be combined.
Here’s a quick comparison to highlight the differences and help delineate the use case for each.
Software Composition Analysis (SCA)
- Identifies all open-source software components
- Uses one or more knowledge bases for comparative analysis
- Offers end-to-end SDLC coverage of the open-source components
- Low false rates for open-source codes
- Fast scans, even with large codebases
- Identifies both security and license compliance risks
Static Application Security Testing (SAST)
- A structural testing methodology based on a set of predetermined rules
- Analyzes source code to uncover security vulnerabilities
- Scans application before the code is compiled
- Detects a high number of false positives in the source code
- Scans can be time-consuming
- Detects a variety of potential code flaw
Both can be deployed early in the SDLC and integrate with CI servers and IDEs. Because of their static nature, SAST and SCA tools cannot clearly define the risk of real-world exploitability due to the vulnerabilities they detect.
Software Composition Analysis (SCA) Supports Open-Source Vulnerability Detection and Mitigation
While SCA isn’t a new technique, its adoption growth mirrors the use of open-source, cloud-native, and containerized software building blocks, making it a foundational pillar for application security.
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