Since the early 2000s, the industry has seen a rapid expansion in open-source adoption. Embracing open source is a strategic decision for cost savings and innovation towards a more collaborative, flexible, and high-quality software development paradigm.
Handling dependencies in software development is crucial and intricate. Developers commonly use external libraries and packages to improve and speed up their work, which can unintentionally lead to security weaknesses and operational dangers in their code. Securing and verifying these external elements is therefore important to keep a strong and safe software environment. A quick online search on “Open Source Risks Exploited at Yahoo, Equifax, Linksys, Uber” highlights the significance of meticulously managing the risks tied to open-source libraries in your organizations.
SCA (Software Composition Analysis) tools are designed to integrate seamlessly into development workflows, providing real-time analysis, automated alerts, and remediation guidance.
Traditional Approach to SCA
SCA tools would scan applications code or build artifacts statically by analyzing dependency manifest files to find the vulnerabilities associated with the included packages. It enables organizations to respond swiftly to emerging vulnerabilities in open-source projects and ensures adherence to legal requirements in software licensing.
Organizations, until very recently, have relied on the traditional SCA to mitigate these risks effectively, which has played a crucial role in dependency management, license compliance, and security assessment.
The primary challenge that organizations face with traditional SCA tools is the security scans report every potential vulnerability linked to the packages in your software, regardless of whether or not these vulnerabilities are relevant or utilized by your applications. This approach can lead to a flood of alerts, many of which might not be relevant, overwhelming developers and leading to alert fatigue. SCA tools might communicate risks and vulnerabilities without sufficient context or guidance on remediation, leading to misunderstandings or misalignment with the development team’s priorities and workflows.
Modern Approach to Manage Open Source Risks
SCA is undergoing two paradigm shifts in the industry: the Call Graph Approach and Runtime SCA.
The call-graph approach statically analyzes the source code and all its used packages to examine the call graphs and data flows.
Runtime SCA instruments the code to derive a dynamic call graph and then combine it with the static call graph and vulnerable method call chains to find more potentially exploitable vulnerabilities
Call Graphs
Call graph-based SCA represents a significant advancement in software security. This approach involves creating a call graph, a visual representation of all function calls within a program. By mapping out these interactions, call graph-based SCA provides a comprehensive view of the software’s structure and behavior. This granularity is particularly effective in pinpointing the exact locations within the code where vulnerabilities may exist based on the actual usage of open-source components.
The transformative aspect of call graph-based SCA lies in its precise and context-sensitive analysis. Traditional SCA tools often provide a broad overview of potential vulnerabilities based on the presence of open-source components without considering how these components are used within the application. Call graph-based SCA, by contrast, offers a detailed understanding of the software’s behavior, highlighting the areas where vulnerabilities could be exploited.
Runtime SCA
Runtime SCA analyzes software dependencies and OS packages in real-time during the application’s actual running. This method dynamically detects and evaluates the actively used open-source components and dependencies, offering a live view of the software’s behavior in its operational environment. Unlike traditional SCA, which assesses dependencies at the development or deployment stages, runtime SCA provides insights based on how the application utilizes these components in real-world scenarios, leading to more precise and context-specific vulnerability identification.
The key advantage of runtime SCA over traditional SCA lies in its enhanced accuracy and relevance in identifying vulnerabilities and prioritizing remediation. Focusing on the components used during the application’s runtime significantly reduces false positives and irrelevant vulnerability reports, enabling developers and security teams to concentrate on genuine threats.
Summary
Both these approaches aligns well with DevOps practices, adapts to changes in application use, and supports a more proactive security posture. It streamlines resource allocation, focusing efforts on fixing critical and directly impactful security issues, thus making the management of software dependencies more efficient and targeted.
