{"id":16837,"date":"2026-10-09T10:05:33","date_gmt":"2026-10-09T10:05:33","guid":{"rendered":"https:\/\/www.kovair.com\/blogs\/?p=16837"},"modified":"2026-10-09T10:08:24","modified_gmt":"2026-10-09T10:08:24","slug":"the-role-of-automation-in-managing-risks-across-modern-software-development","status":"publish","type":"post","link":"https:\/\/www.kovair.com\/blogs\/the-role-of-automation-in-managing-risks-across-modern-software-development\/","title":{"rendered":"The Role of Automation in Managing Risks Across Modern Software Development"},"content":{"rendered":"\n
\"Software<\/figure>\n\n\n\n

Modern software development is all about constant modifications to code, dependencies from open source software, use of cloud computing services, application programming interfaces, containers, automated tests, and now more and more often, use of AI for development purposes. These features make software development more efficient and scalable, but at the same time they pose risks that are hard to detect and manage without automation. Thus, automation is gaining importance as a means of managing software risks.<\/p>\n\n\n\n

In its Secure Software Development Framework (SSDF), NIST highlights the importance of embedding security practices into development processes and mentions that automatability is one of the criteria that should be taken into account when adopting security practices on a large scale. The same tools are also contributing to the risk management market as a whole, as its demand becomes increasingly associated with continuous monitoring and vulnerability detection.<\/p>\n\n\n\n

Automation Is Changing How Software Risks Are Managed<\/strong><\/h2>\n\n\n\n

Traditionally, risk management was based on audit and testing along with security assessments carried out during certain stages of software development process. Modern software development, however, is dynamic in its nature, making point-in-time assessments ineffective in terms of identifying risks emerging between audits. Due to automation, continuous or trigger-based controls are established which operate in parallel with the development process. This makes it possible to assess risks either at the end of the application development, or when changes occur in code checking, dependencies or infrastructure.<\/p>\n\n\n\n

Continuous Code Analysis Identifies Vulnerabilities Earlier<\/strong><\/h3>\n\n\n\n

Patterns that relate to security holes, bugs, and security bad practices in the source code are identified using source code analysis. Source code analysis can occur in the development process and give findings that are closer to where the change happened.<\/p>\n\n\n\n

Factor: Earlier Risk Identification;<\/strong> Automated code analysis allows earlier identification of a risk that was introduced. Early detection gives developers better understanding of the change related to a finding.<\/p>\n\n\n\n

Automation Strengthens Software Supply-Chain Risk Controls<\/strong><\/h3>\n\n\n\n

Using open-source libraries, commercial software components, containers, third-party APIs, and development tools is a common approach used by modern software applications. The use of the above approach results in the creation of a software supply chain, which is longer and, therefore, makes it more likely that any vulnerability identified outside the source code of the company may have an impact on the software. There are several practices included in the NIST SSDF that address the issue of software component security, secure software delivery, and vulnerability management, while OWASP considers the CI\/CD infrastructure.<\/p>\n\n\n\n

Dependency Monitoring Tracks Third-Party Exposure<\/strong><\/h3>\n\n\n\n

Dependency management automation software may be able to detect what software packages are being utilized by the application and check whether these software packages are vulnerable. It is vital to note that this becomes very important as developers update their dependencies on a regular basis.<\/p>\n\n\n\n

Factor: Expanding Dependency Exposure;<\/strong> Each external component introduces another element requiring visibility and assessment. Automated dependency monitoring provides a repeatable mechanism for identifying known vulnerabilities across software inventories.<\/p>\n\n\n\n

Software Bills of Materials Improve Component Visibility<\/strong><\/h3>\n\n\n\n

Bills of materials for software products are structured documentation that describes the components used in those software products. If the bill of materials is accompanied by inventory and vulnerability scanning tools, it allows for quick identification of applications potentially affected by a component vulnerability.<\/p>\n\n\n\n

Factor: Component Traceability<\/strong>;<\/strong> Automation makes inventory more explicit in the relationship between application and the underlying component. This provides the means for vulnerability research and determining where remediation is needed.<\/p>\n\n\n\n

Automation Protects CI\/CD Pipelines and Build Environments<\/strong><\/h3>\n\n\n\n

Automation is critical to CI\/CD as far as compiling, testing, packaging, and deployment of software goes. OWASP considers CI\/CD pipelines to be very automated processes and highlights the significance of their role within the current software development life cycle, but also stresses the fact that such significance can make them vulnerable to attack.<\/p>\n\n\n\n

Pipeline Controls Detect Unauthorized Changes<\/strong><\/h3>\n\n\n\n

Automated controls for pipeline management may be able to analyze any changes to the build configurations, workflows, permissions, and deployment processes. Analysis of such items gives insight into changes that may impact software delivery.<\/p>\n\n\n\n

Factor: Pipeline Integrity Monitoring;<\/strong> Development pipelines have access to source code, build systems, artifacts, and deployment environments. Automated monitoring helps identify unexpected changes to these critical processes before they affect subsequent stages.<\/p>\n\n\n\n

Automated Artifact Verification Protects Software Integrity<\/strong><\/h3>\n\n\n\n

Builds can generate software artifacts that go through test, staging, and production environments. The processes of integrity checking, signing, and verification help control whether there are any changes to the artifacts while they are being transferred through the delivery channel.<\/p>\n\n\n\n

Factor: Artifact Tampering Detection;<\/strong> A software artifact that changes unexpectedly may indicate an integrity problem within the delivery process. Automated verification establishes consistent checks between artifact creation and subsequent deployment activities.<\/p>\n\n\n\n

Automation Extends Risk Management into Deployment<\/strong><\/h2>\n\n\n\n

The risk remains after the software passes through development and testing stages. This is because even after deployment, the applications will continue to interact with end-users, cloud resources, database, identity, API, and other third-party systems.<\/p>\n\n\n\n

Runtime Monitoring Detects Emerging Threats<\/strong><\/h3>\n\n\n\n

Runtime Monitoring is concerned with monitoring the activities related to the applications themselves, network activities, authentication activities, system configuration, etc. This will help identify any anomalies in activities that may not be easy to detect at the development stage.<\/p>\n\n\n\n

Factor: Continuous Runtime Visibility;<\/strong> The behavior of software applications may change even after deployment owing to new users, integrations, configurations, etc. Runtime Monitoring provides another means of gathering data about unusual activities.<\/p>\n\n\n\n

Automated Alerts Support Faster Response<\/strong><\/h3>\n\n\n\n

Larger software environments may produce large amounts of security-related data and operational information. Automatic notification mechanisms can recognize certain criteria being met and then dispatch relevant events for analysis by security and\/or operational teams.<\/p>\n\n\n\n

Factor: Faster Risk Escalation<\/strong>;<\/strong> Automated alerts reduce dependence on continuous manual observation of security events. Structured escalation also helps teams prioritize events that require further analysis according to established organizational criteria.<\/p>\n\n\n\n

Excessive Automation Privileges Increase Exposure<\/strong><\/h3>\n\n\n\n

Automation often demands access to repositories, clouds, credentials, databases, and deployment systems. Any permission above the minimum required could be enough for a possible breach in the automation system to lead to access to several components of the software environment.<\/p>\n\n\n\n

Factor: Automated Privilege Exposure;<\/strong> <\/strong>Automation needs to be configured using specified permission settings, since one software can interact with many systems simultaneously. The concepts of role-based access control, credential management, and least privilege principle can assist in mitigating the risk that may arise from automation system penetration.<\/p>\n\n\n\n

The Impacts of Automation in Risk Management in the Era of Increased Connectivity and Continuity of Software Development<\/strong><\/h2>\n\n\n\n

Automation is affecting the way software risk management works by integrating security controls and risk management at all levels of code development from dependencies, testing, build, deployment, and runtime. Instead of relying on assessments after the development process, more and more companies are moving toward automation in the identification of vulnerabilities, configuration management, software supply chain security, and response to emerging risks.<\/p>\n\n\n\n

With increasing decentralization of software development processes, the software risk management market<\/a> will become more integrated with assessment, compliance, and vulnerability management automation. This trend is captured by Pristine Market Insights, which sees an increasing reliance on automation for increased visibility into software development processes. Nonetheless, automation serves as a supplementary control measure.<\/p>\n

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