As AI integrates into every stage of the SDLC, the area of software testing is undergoing transformative and unprecedented changes. In this article, we will discuss the ethical considerations for AI-powered software testing, examining the advantages and potential hurdles generative AI presents as a new technology being applied across the SDLC.

Static code analysis is widely adopted among organizations for its ability to provide fast feedback loops and identify bugs early in development. However, despite its advantages, numerous bugs and vulnerabilities remain undetected and are only found when they've made their way into production or been caught by late-stage penetration testing. The best security practice involves leveraging both static and dynamic testing, such as fuzz testing.

As vehicles become increasingly reliant on software, secure and functional Hardware Security Modules (HSMs) are paramount. Unknown vulnerabilities in your automotive software can pose a significant threat to your products and business by putting you at risk of coding errors or insecure configurations, which can be exploited by malicious actors or lead to consequential failures.

In today's digital and interconnected era, the healthcare sector operates in a landscape of security risks. In 2023 alone, the number of vulnerabilities uncovered in medical devices jumped by 59% to 993 issues. Consequently, the U.S. Food and Drug Administration (FDA), the European Commission, and other governmental agencies have issued cybersecurity guidelines for medical devices. Many of these guidelines advocate for fuzz testing as a means of vulnerability detection.