A Developer’s Guide to Running an SCA Scan

Your IT infrastructure is a complicated network of systems and activities that generate massive volumes of data every second. Hidden within this data stream is the key to understanding your systems’ health and potential dangers.

The dangers are significant, given that the average worldwide data breach costs an exorbitant $4.45 million. One such security breach can destroy your organization, resulting in legal fines, financial loss, and harm to your reputation.

If you want to navigate this difficult terrain, you will need the right tools to analyze and interpret your logs. That’s why Software Composition Analysis (SCA) has become integral to modern software delivery pipelines. It is aimed to help mitigate these security risks and help you gain a bird’s eye view of running such scans.

What is SCA Scan?

SCA scan is a process for tracking and analyzing a software application’s source code for security vulnerabilities introduced by importing open-source software packages. 

These packages can be third-party libraries or embedded components that eventually become part of the software application shipped and deployed for its intended commercial usage. Therefore, any vulnerability discovered in these packages also poses a security risk for the overall application. An SCA scan helps identify and address such vulnerabilities within the packages and other dependencies.

SCA scans form an important stage of any software development process lifecycle, wherein they are integrated into a project’s CI/CD pipeline. This way, developers and security teams can flag open-source security vulnerabilities early in the development cycle, who are the primary stakeholders benefiting from this process.

Therefore, the SCA scanning process is essential for enforcing secure coding and development practices in the larger software development process before the source code is deployed in production. 

How Do SCA Scans Work?

At a high level, SCA scans rely on a series of operations. It all starts with parsing. As part of the parsing operation, the SCA tool parses the source files, configuration files, and other artifacts, including binary files, container images, and deployment definition files.

The primary purpose of the parsing operation is to build a software bill of materials (SBOM). The SBOM is a single source of truth for all the open-source and third-party packages in a codebase and includes additional metadata about the packages, such as versions and license types.

The other critical aspect of an SCA scan is matching the SBOM with vulnerability databases. These databases contain all the knowledge about open-source packages and their reported security vulnerabilities. 

Finally, the outcome of the SCA scan is made available to the stakeholders through various reporting mechanisms, which list all the identified packages and their vulnerability and risk status.

Types of SCA Tools

Since developers are the primary users of SCA tools, it is best to evaluate them based on the integration options with the developer workflow. Accordingly, you can think of three categories.

1. Standalone: These SCA tools are standalone software or web services with a CLI or a web-based dashboard interface for manually triggering SCA scans. 
2. CI/CD Integrated: These SCA tools offer tighter integration options with the CI/CD pipeline, over and above the standalone usage, to automatically trigger SCA scans at various points within the pipeline.
3. AppSec Integrated: These SCA tools are part of larger application security platforms. In this case, SCA scanning is combined with static and dynamic security testing to build comprehensive security coverage for the application software.

Guide To Running an SCA Scan    

SCA plays a vital role in modern DevSecOps practice. Here, the typical DevOps cycle is customized to include SCA scans within the pipeline. This approach provides development and operations teams with early warnings about impending vulnerabilities and ensures security visibility during coding and build phases.

From a developer’s point of view, running an SCA scan is a straightforward process. 

The only precondition is granting access to the source code repository or the filesystem containing the code base. This entire process of running an SCA scan can be broadly divided into five steps.

Step 1: Triggering the SCA scan

Triggering an SCA scan can be done manually or in an automated way.

The manual trigger is done by launching the SCA tool software and pointing it to the repository. It is suitable when developers want to double-check for vulnerabilities introduced due to newer dependencies as part of their ongoing coding activities.

In the case of the automated trigger, the SCA tool is triggered based on specific CI/CD pipeline events, such as a pull request. These triggers spawn an SCA agent, which executes as part of the CI/CD pipeline processing.

No matter how the SCA scan is triggered, the developers can always see the details of the ongoing (and historical) SCA scans in the SCA tool’s dashboard or query from the CLI, depending on the tool’s user interface.

Step 2: Identification of Dependencies

In this step, the SCA tool scans the source code and parses the package definitions from the relevant source files to identify the open-source or third-party packages.

This step runs in the background. It does not require any action from the developer.

Step 3: Building the SBOM

Once the identification is complete, the SCA tool creates an inventory of the packages and assembles them as an SBOM, including each package’s version, dependencies, and license information.

This is also a background step that continues the previous identification step. However, at the end of this step, depending on the capabilities and settings of the SCA tool, the developers can export the SBOM with the complete list of open-source packages and other third-party packages identified during the previous step.

Step 4: Matching And Detection Of Vulnerabilities

After the SBOM is finalized, the SCA tool analyses each package for possible vulnerabilities by comparing it against various vulnerability databases, such as the National Vulnerability Database, an open database maintained by the US government. Similarly, the SCA tool can also be configured to match with other public and private databases maintained by the various organizations.

While this step also happens in the background, the developers can check the vulnerability detection progress through real-time updates in the SCA tool’s dashboard with details of matched packages flagged for security risks in the ongoing SCA scan. During this step, developers must keep an eye on the dashboard to check for certain exceptions in SCA scanning, such as:

1. False positives/negatives: These exceptions happen when the SCA tool identifies vulnerabilities in dependent packages that do not pose any risks or vice versa.
2. Unknown packages: This is when a dependent package has no record or history in the vulnerability databases. It can also happen due to legacy software or name confusion attacks.
3. Transitive dependencies: These are chained dependencies that cause a fan-out effect. As a result, multiple low-risk, secondary dependencies are identified with vulnerabilities, and the SCA tool’s output is inundated with such packages, leading to confusion.

Step 5: Report Generation

At this stage, the SCA scan is complete with findings based on parsing and matching the packages with vulnerability databases. Developers can export these findings through SCA scan reports.

SCA tools offer several reporting options, such as:

1. SCA report document: At the end of each SCA scan, the developers can manually generate the report document from the SCA tool’s dashboard. 
2. Code comments or issues: In the case of an automated trigger from the CI/CD pipeline, the SCA scan findings are added in comments within the source code or issues directly raised on the repository.
3. Formatted output: The SCA tools also offer export options in well-known formats, such as XML and JSON, which can be opened within the IDE or other software for further analysis and tracking.

Many SCA tools offer vulnerability remediation, which provides further insights. This feature can be considered a post-reporting step for analyzing the exploitability, severity, and effort of fixing each vulnerability.  These insights help developers save time on vulnerability investigations and help prioritize the fixes for high-risk vulnerabilities.

Embrace Secure Coding Practices with SCA

Modern software development is characterized by high-velocity sprints, which necessitate reliance on external, open-source software packages to avoid reinventing the wheel and achieve faster release cycles.This strategy has some security concerns along with its many advantages. Malicious packages and vulnerabilities can easily find their way into your codebase and compromise the security of your applications.

To prevent these risks, a strong security approach should involve both Software Composition Analysis (SCA) and thorough code review techniques. SCA tools such as Spectral assist in identifying and addressing vulnerabilities in open-source components, whilst code review guarantees adherence to best practices and detects potential concerns early in the development process.

With it, developers can focus on their core competencies, and security teams have a single window to track the provenance and remediation of all vulnerabilities without wasting hours. 
Ready to level-up your coding practices? Get started now with a free account and learn more about Spectral’s SCA capabilities.