Open-source software presents specific advantages and disadvantages for development teams. The practicality of using established software components can save development teams time and effort. However, the use of outside, third-party, and open-source software components can present its own set of risks, vulnerabilities, and concerns over compliance and governance. To mitigate these concerns, security testing is vital. Software composition analysis (SCA) tools help development and infrastructure teams inspect outside software and resolve potential risks before they impact the business.
What is software composition analysis (SCA)?
According to one study, up to 84% of codebases contain at least one open-source vulnerability. Software Composition Analysis (SCA) tools scan your codebase to find open-source components, check for vulnerabilities, and flag licensing issues. Development teams, DevOps, and managed services utilize SCA to ensure security, compliance, and governance by tracking dependencies, identifying risks, and providing actionable insights to manage third-party software components throughout the entire software lifecycle.
Why is software composition analysis critical?
Open-source software accelerates development by enabling teams to build applications with pre-built code but increases risks in security, compliance, and governance. Testing for vulnerabilities is also harder due to more components and tighter integrations.
The adoption of SCA tools is critical in areas such as:
Security risk mitigation: SCA tools can detect known vulnerabilities in open-source components before they can be exploited, thereby reducing the risk of security breaches.
Compliance assurance: Utilizing SCA tools ensures adherence to licensing obligations and legal requirements by identifying non-compliant licenses and ensuring alignment with organizational policies.
Transparency: Integrating SCA tools in the software development lifecycle provides teams with visibility into third-party dependencies across applications, identifies and resolves issues before release, and reduces costs and complexity.
Efficiency: SCA tools can automate testing, detection, and tracking, reducing manual auditing efforts within continuous integration/continuous delivery (CI/CD) pipelines.
Reputation protection: SCA tools can reduce the risk of insecure libraries, provide traceability for software components, and monitor code licenses to ensure compliance with governance and legal requirements.
How software composition analysis works
SCA tools continuously scan and monitor each application’s codebase for open-source libraries and third-party components. This scan checks against databases that maintain detailed inventories of open-source libraries containing vulnerabilities such as security risks, outdated code, and licensing concerns.
SCA consists of the following steps:
Scanning: Tools analyze source code, build artifacts, and container images to identify open-source components. SCA tools might use static scanning, which examines build manifest files such as package.json or pom.xml during an application’s build process, or dynamic scanning (also known as binary scanning), which inspects application binary code in real time. SCA tools can also use both scanning methods.
Identification: SCA tools compare components against databases of open-source libraries and vulnerabilities (such as the National Vulnerability Database [NVD]). SCA tools can also compare open-source libraries to Common Vulnerabilities and Exposures (CVE) lists maintained by the CVE Program, which track cybersecurity vulnerabilities.
Analysis: Tools evaluate component metadata, versions, licenses, and risks. SCA tools examine and review manifests, binaries, and licenses for open-source and third-party components that match vulnerability lists.
Reporting: Tools offer dashboards that highlight vulnerabilities or non-compliance. SCA tools generate detailed reports that list component names, versions, licenses, and known vulnerabilities. They can also continuously monitor for new threats, providing alerts for newly discovered issues.
Remediation: Tools recommend safer versions, patches, or alternative dependencies. SCA tools also evaluate the health and maintenance of components, identify abandoned or outdated packages, and help enforce security and compliance policies by preventing the deployment of non-compliant components.
Integration: Often embedded in CI/CD pipelines and development environments, SCA tools enable automated, continuous monitoring. They facilitate automated, real-time scanning during code commits, pull requests, and builds.
Some other SCA practices to consider:
An SCA tool should seamlessly integrate with your organization’s existing development workflow. Incorporating SCA into CI/CD pipelines enables developers to prioritize application security easily.
Automated scans actively check and monitor code for errors. An SCA tool should allow you to run these scans consistently throughout the software development cycle.
The SCA tool should provide accurate reports that include detailed summaries of components and offer better insights into dependencies.
Establish guidelines to protect your software. For example, SCA tools can categorize vulnerabilities or license types based on compliance levels and prevent specific components from being deployed.
Who benefits from software composition analysis?
Organizations benefit from software composition analysis (SCA) tools by gaining insight into open-source and third-party components, enabling them to identify and manage risks associated with these components. SCA tools help organizations address security vulnerabilities, ensure license compliance, and bolster their software security. This is especially crucial for sectors that handle sensitive data, such as finance, healthcare, and government, where the dangers of insecure software are particularly high.
SCA tools support multiple teams:
Security teams: For monitoring vulnerabilities in dependencies. Continuous scanning and early detection of vulnerabilities support DevSecOps and security strategies.
Developers: To ensure secure and compliant code from the start. By integrating SCA into their development environments and CI/CD pipelines, developers can future-proof their code against potential security risks, licensing issues, and compliance concerns.
Legal/compliance officers: To manage license risks and open-source use, ensuring software applications are secure and compliant.
Executives: Any organization that uses or develops software applications can utilize SCA to reduce business risk from supply chain attacks. The widespread use of open-source components makes manual tracking impractical, and automation is crucial for effective risk management.
Use case scenarios for software composition analysis
Examples of use cases for SCA include:
Pre-deployment checks: Scanning applications before release can help prevent vulnerable dependencies from going live. SCA tools help teams identify and fix issues early, reducing the chance of vulnerabilities reaching production.
Continuous monitoring: SCA tools integrated into CI/CD pipelines enable security checks to happen early and continuously during development and before deployment, which can help organizations detect new vulnerabilities in deployed components.
Audit readiness: SCA tools review open-source component licenses and compare them to company policies to demonstrate compliance with security and licensing standards and find conflicts, such as using a GNU General Public License (GPL)-licensed library that requires derivative works to be open-sourced.
Incident response: SCA tools integrated with CI/CD pipelines automate vulnerability detection, significantly reducing response times during security incidents and quickly evaluating exposure when a new zero-day vulnerability is announced.
Datadog Software Composition Analysis helps identify vulnerable open-source libraries in production as teams monitor overall service health, ensure remediated vulnerabilities reach production, and prevent discrepancies between static and runtime code caused by CI/CD pipeline errors.
Common implementation challenges for software composition analysis
SCA testing is neither foolproof nor a guarantee that specific vulnerabilities can be found. SCA tools do not cover the entire security surface and can miss proprietary code vulnerabilities and runtime issues. Some SCA tools mainly focus on pre-production environments. Some additional challenges users might face when using SCA tools include:
False positives: Excessive or inaccurate alerts can overwhelm teams, resulting in unnecessary workload. False positives can arise from unused dependencies (such as test harnesses) that are included in scans but never executed, leading to alert fatigue and reduced trust in the tool.
Complex dependencies: Large modern applications often have hundreds of transitive dependencies. These dependencies might be skipped or overlooked due to environment-specific definitions and incomplete dependency lists, potentially missing vulnerabilities in deeply nested libraries.
Performance overhead: Scans can slow down builds if not optimized. Integrating SCA into fast-moving CI/CD pipelines can slow builds or frustrate developers if not implemented with performance in mind, potentially causing workflow disruptions.
Remediation burden: Addressing vulnerabilities might require extensive refactoring. Some SCA tools do not provide actionable remediation guidance, such as automated pull requests for updates.
Tool fragmentation: SCA tools vary in coverage and accuracy, necessitating careful choice. A lack of clear ownership and cross-team collaboration among security, development, and operations can hinder adoption and lead to inconsistent implementation.
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With real-time observability, Datadog SCA enables DevOps and security teams to identify and prioritize critical vulnerabilities, promptly preventing costly breaches, and helps apply recommended fixes for quick resolution.
