Application security testing tools are designed to ensure that applications are put through rigorous security assessments to identify security flaws within the application and its code. Even though applications are tested thoroughly (in static and dynamic ways), attackers always seem to find new ways of compromising them. Some of these sophisticated attacks target the vulnerabilities found within third-party libraries, which became ubiquitous since the early days of the cloud; a wide range of SCA vendors addressed this attack vector throughout the years.
What is SCA?
Software Composition Analysis (SCA) is a set of practices and tools designed to identify and manage open-source and third-party components used in a software application. As modern software development often involves the integration of existing libraries, frameworks, and components, it becomes crucial to understand and manage the composition of the software to ensure security, licensing compliance, and overall software health.
Traditionally, SCA tools relied on static analysis of code repositories. Nowadays, SCA has expanded to incorporate non-static data, namely data that originates from the application’s runtime. Runtime SCA has inherent advantages over traditional, static SCA tools, as data from the runtime is by definition more accurate and comprehensive. By looking at the actual behavior of the application, it is possible to determine which vulnerable components are actually used and how which in many cases cannot be done statically.
Let’s explore the challenges of Traditional SCA.
Challenges with traditional SCA
1. Long lists of vulnerabilities
Having visibility into all aspects of an application and its vulnerabilities is crucial. However, this process often creates a staggering number of vulnerabilities, sometimes in the thousands. The sheer number of these vulnerabilities detected with traditional software composition analysis tools overwhelms security and development teams that are tasked with remediating them – even though many of those vulnerabilities are actually not deployed, used or impose any risk. This may result in overlooking critical vulnerabilities that may severely impact the application.
2. High number of false positives
Traditional SCA tools are notoriously known for the number of false positives they provide. Some of the reasons for such false positives are:
- Vulnerabilities in Dead Code: Imagine an SCA tool flagging a vulnerability within a code segment that is, in fact, part of dead code – portions of the application that are never executed during runtime. Such vulnerabilities might be technically present in the codebase, but since they are never triggered in practice, they pose no actual threat to the application or its users. These false positives can lead to unnecessary alarms and waste valuable resources in addressing non-issues.
- Overzealous Identification of Component Vulnerabilities: SCA tools may occasionally identify vulnerabilities in libraries or third-party components that, upon closer examination, do not pose a real risk. For instance, a tool might flag a component as vulnerable due to an outdated version, even if that specific component isn’t utilized in a way that exposes the vulnerability in the application. This can result in the security team dedicating substantial effort to validate findings that ultimately don’t require immediate attention.
In these cases, security teams must validate all the findings to ensure each vulnerability is valid. The false positives combined with the many vulnerabilities require an enormous team effort to complete the validation process.
3. Accumulation of a backlog of vulnerabilities
Developers operating at a smaller scale can remediate most of the findings. However, when the application scales, or if there are multiple applications involved, the sheer effort required to remediate these findings increases significantly up to a point where most of the findings will be left unhandled.
The accumulation of vulnerabilities inadvertently will create a backlog, thus further increasing the risk of open source library vulnerabilities being exploited by a threat actor.
4. Friction between development and security teams
These problems often create a challenge across development and security teams. Developers are forced to shift their attention from core development tasks to address vulnerabilities that may not pose a real risk. This can lead to pushback from developers in some cases or to project delays and decreased productivity.
Furthermore, issues arise between development and security teams regarding the severity of identified vulnerabilities, particularly when development teams are inundated with numerous false alarms.
To mitigate these issues, effective communication and collaboration are essential to prioritize genuine security risks and ensure that the development process remains smooth.
Runtime Insights: Key to Addressing Traditional SCA Challenges
Runtime insights are the signals extracted by monitoring and analyzing software applications and their components in runtime.
Reduced False Positives
It provides results on a real-time basis as the application is running but also helps organizations distinguish between genuine threats and false positives. For example, it can show that a certain vulnerable function is never invoked in production, thus reducing its risk significantly. This increased accuracy in threat detection streamlines security operations and minimizes time wasted on investigating non-existent issues.
Improved Vulnerability Prioritization
Runtime insights provide valuable context for prioritizing vulnerabilities. For example, it can show the exact Kubernetes cluster in which a vulnerable function was invoked. Security teams can assess vulnerabilities based on their potential impact on live applications, allowing them to allocate resources more effectively to address the most critical issues first.
Reduced Friction Between Sec and Dev
The forensics provided by runtime insights can significantly improve security teams’ ability to demonstrate the importance of fixing these vulnerabilities. When developers are able to see the risks in the context of their system, it helps bring them on board much easier.
Conclusion
Software Composition Analysis (SCA) tools have played a vital role in enhancing security, but have always been known to be limited and not without flaws. Enhancing these tools with data from the runtime can mitigate many of these issues. By doing so, modern application security assessments will go beyond just highlighting vulnerabilities; they will provide real-time insights into applications and their components. By reducing false positives and allowing vulnerabilities to be prioritized effectively, we can ensure that our systems remain resilient to potential threats that may arise.
