The ASOC platform is a powerful tool for adopting DevSecOps, enabling companies to not only establish secure development processes but also automate them as much as possible. The integration of artificial intelligence and machine learning significantly reduces manual work and accelerates the delivery of software to the market. ASOC tools are at the forefront of DevSecOps developments. They can address security concerns for software of any architecture and complexity without impacting delivery speed.
#The rise of cybercrime, combined with the urgent need for new products and a push to accelerate development, makes the adoption of DevSecOps critical. Industry analysts note that approximately 77% of development teams have adopted this approach. Today, more and more enterprises are opting for Application Security Orchestration and Correlation (ASOC) within the DevSecOps framework to ensure secure software development.
ASOC-type DevSecOps system
DevSecOps stands out from traditional development methods by integrating security into every stage of software creation from the beginning. There are many ways to adopt DevSecOps. For those who wish to avoid complex setups, the market offers ASOC-based solutions. These solutions help companies save time, money and labor resources while also reducing product time to market.
The ASOC platform enhances the effectiveness of security testing and maintains the security of software in development without delaying delivery. Gartner's 2021 Application Security Hype Cycle indicates that these solutions will have market penetration between 5% and 20% among target customers. Actual adoption of this technology is low, mainly due to limited awareness of its usability and benefits.
ASOC solutions integrate application security testing (AST) tools into existing CI/CD pipelines, facilitating transparent, real-time collaboration between engineering teams and information security experts. These platforms provide orchestration capabilities, meaning they set up and execute security pipelines and perform relevant analysis on issues identified by AST tools, further aggregating this data to gain comprehensive insights.
ASOC tools can generate documentation and reports on security and related business risks based on analysis. By orchestrating and correlating within a DevSecOps framework, they can process large amounts of data from development, testing, and security processes in real time. This rich information supports the platform’s dynamic feedback loop, allowing intelligent oversight of the entire security software lifecycle.
Intelligent Control Settings
Data analysis tools can be integrated into ASOC-like platforms through the development of add-on modules dedicated to integrating, storing and analyzing collected information. How it's done:
1. Collect data from software development and security scanning tools and upload it to a dedicated data warehouse.
2. Establish a set of indicators derived from the collected data.
3. Put business context into these metrics and identify key performance indicators (KPIs).
4. Create dashboards to manage the DevSecOps platform using raw data, metrics, and KPIs.
Artificial intelligence and machine learning are revolutionizing the way we analyze the data we collect, allowing us to quickly adapt to changes and improve software delivery processes. In order to take advantage of the intelligent management of the ASOC platform, the implementation steps of the data processing module can be adjusted. The initial three steps remain the same, but the fourth involves using artificial intelligence and machine learning to process raw data, metrics and KPIs. This enables the creation of dashboards that simplify management of the DevSecOps platform based on enhanced data analytics.
Through the lens of ASOC practices, artificial intelligence and machine learning significantly improve the efficiency of orchestrating and correlating tasks.
Orchestration
Automated Software Quality Assurance
Artificial intelligence in ASOC-level platforms intelligently extracts data from collected data and Components and criteria required for each checkpoint are dynamically set in a metric pool to evaluate software quality. This AI-driven approach to defining quality control points lets you know whether a build is ready for the next phase of its lifecycle. Leveraging AI, you can move artifacts through the DevSecOps pipeline with maximum automation. Make progress decisions after scanning builds in different environments, paving the way for fast and consistent releases.
Automated quality control checkpoints can cover a variety of application security testing practices. The configuration of these checkpoints can be dynamically adjusted based on the stage of the security pipeline. Therefore, it is feasible to establish checkpoints and customize their criteria in CI/CD pipelines, thus providing a powerful means to monitor and manage software quality.
CI/CD Pipelines as Code
For large-scale DevSecOps implementations, managing CI/CD pipelines as code has clear advantages. Companies that adopt this strategy gain a powerful tool to enhance their software deployment, launch, management, and monitoring processes. Modern ASOC solutions build secure pipelines “out of the box” with the click of a button. Artificial intelligence and machine learning technologies improve this by automatically identifying software components and setting up CI/CD pipelines that meet precise quality standards.
AI assists in cataloging software artifacts, automatically setting up end-to-end pipelines, and proactively integrating calls to information security tools while being guided by the context and various parameters of the product being developed. Artificial intelligence technology within the ASOC framework can also dynamically adjust the order and number of software quality control checkpoints within each CI/CD pipeline. This approach significantly speeds up product releases because the entire process, from initial submission to release of the final version, is carefully overseen.
Correlation
Application Vulnerability Correlation
ASOC technical support creates the Application Vulnerability Correlation (AVC) mechanism, which Mechanisms use data from software testing tools to correlate security issues. This process involves an ML model that automatically sifts through the noise to eliminate false positives, find duplicates and similar security issues, and then merge them into a single identified flaw.
This mechanism significantly reduces the time required to resolve security issues, allowing teams to focus on critical vulnerabilities and increasing the speed of threat detection in the software they develop.
Quick Fix Guide for Software Vulnerabilities
Any detected problem set always contains common vulnerabilities, including some critical vulnerabilities that can be easily fixed. AVC technology identifies and ranks information security vulnerabilities and provides automated recommendations on how to fix them.
The ASOC platform collects vulnerability data from a range of security scanners, including SAST, SCA, DAST, and more. Generate secure code templates by integrating AVC technology and providing it with comprehensive standards and detailed secure coding recommendations. These templates are customized to fit the specifics of a company's DevSecOps implementation, further enhancing security measures.
Simplifying Security Compliance Management
In software development, compliance with industry security standards and regulatory requirements is always a critical aspect. The process of managing these requirements can be fully automated throughout the product lifecycle, streamlining task execution within the company.
Automated checks help ensure all standards and requirements are met. With the ASOC platform, artificial intelligence and machine learning technologies can leverage software quality checkpoints and predictive analytics to continuously monitor security compliance. This monitoring provides the development team with a clear judgment as to whether the software being developed meets the necessary standards.
Evaluate the return on investment of the ASOC platform
Investing in the ASOC platform requires evaluating the potential return on investment (ROI), which includes considerations of cost, time savings, and improved security . Evaluate ROI:
1. Cost savings: Calculate the cost savings due to the reduction in the need for manual security testing and the potential reduction in security incidents and vulnerabilities.
2. Time efficiency: Evaluate the time saved by automating security testing and integration in CI/CD pipelines. Detecting and fixing vulnerabilities faster accelerates development cycles.
3. Improve security: Consider the value of a stronger security posture, including the potential to avoid regulatory fines, protect brand reputation, and ensure customer trust.
4. Scalability: Assessing the ASOC platform’s ability to scale with your development needs may provide greater long-term value as your organization grows.
Conclusion
The ASOC platform is a powerful tool for adopting DevSecOps, allowing companies to not only establish secure development processes but also automate them as much as possible. The integration of artificial intelligence and machine learning significantly reduces manual work and accelerates the delivery of software to the market.
ASOC tools are at the forefront of DevSecOps evolution. They can address security concerns for software of any architecture and complexity without impacting delivery speed.
However, not many organizations understand the ASOC platform. This has led many companies to stick with traditional, less scalable approaches to implementing DevSecOps through isolated automation efforts. Nonetheless, the market already offers effective solutions that can significantly ease the workload of software professionals. ASOC platforms powered by AI/ML technology merge security analytics and management into existing DevOps workflows, significantly reducing DevSecOps implementation time to just weeks.
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