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Interest in DevSecOps has increased due to its role in integrating security into the software development lifecycle. This integration addresses vulnerabilities from fast code generation, especially with AI tools. Traditionally, development, operations, and security teams worked separately, leading security assessments to occur just before software release. The rise of DevSecOps incorporates security earlier in the development process. The demand for security tools rises as AI-generated code often contains exploitable bugs, prompting organizations to invest in automated security tools like static application security testing (SAST).
Developers rely more on open-source code, which adds risk due to dependencies on third-party components. A notable example is the Log4j library, which had a significant vulnerability. To mitigate these risks, tools such as Software Composition Analysis (SCA) analyze third-party component security. Increased software release frequency, driven by continuous deployment practices, can result in "security debt" if vulnerabilities are not managed properly. Startups must adopt security measures similar to those of larger companies as B2B SaaS customers expect compliance with standards like SOC2 Type 2, which requires a robust security program. As software development evolves, incorporating security closer to development is essential, emphasizing the need for efficient security tools.
Learn more on this news visit us at: https://theweb3.news/news-bites/why-is-devsecops-the-key-to-secure-ai-development/
Hosted on Acast. See acast.com/privacy for more information.
Interest in DevSecOps has increased due to its role in integrating security into the software development lifecycle. This integration addresses vulnerabilities from fast code generation, especially with AI tools. Traditionally, development, operations, and security teams worked separately, leading security assessments to occur just before software release. The rise of DevSecOps incorporates security earlier in the development process. The demand for security tools rises as AI-generated code often contains exploitable bugs, prompting organizations to invest in automated security tools like static application security testing (SAST).
Developers rely more on open-source code, which adds risk due to dependencies on third-party components. A notable example is the Log4j library, which had a significant vulnerability. To mitigate these risks, tools such as Software Composition Analysis (SCA) analyze third-party component security. Increased software release frequency, driven by continuous deployment practices, can result in "security debt" if vulnerabilities are not managed properly. Startups must adopt security measures similar to those of larger companies as B2B SaaS customers expect compliance with standards like SOC2 Type 2, which requires a robust security program. As software development evolves, incorporating security closer to development is essential, emphasizing the need for efficient security tools.
Learn more on this news visit us at: https://theweb3.news/news-bites/why-is-devsecops-the-key-to-secure-ai-development/
Hosted on Acast. See acast.com/privacy for more information.