AI is changing security testing, but not all vulnerabilities are created equal
Artificial intelligence is rapidly reshaping cybersecurity. Much of the conversation has focused on how large language models are helping developers write code, but a more significant shift may be occurring elsewhere: security testing.
AI systems are becoming remarkably effective at identifying vulnerabilities, forcing organizations to rethink how they evaluate the security of both software and hardware products.
Vice President of Product Security & Innovation at PQShield.
The reason lies in the nature of modern software. Large codebases are sprawling ecosystems of interconnected modules, third-party dependencies, legacy components, and undocumented assumptions.
Security flaws often emerge not from a single defective function, but from subtle interactions between components that may be separated by hundreds of files or years of development history. Human reviewers excel at deep analysis, but they are constrained by time and cognitive bandwidth.
AI systems, by contrast, can rapidly traverse vast amounts of code, correlate information across repositories, and...
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