Since 2023, Google has introduced large language models into security fuzz testing, subsequently collaborating with Project Zero and DeepMind to develop vulnerability discovery agents like Naptime and Big Sleep. Historical trends show its continuous integration of AI into the entire process from discovery, reproduction, classification to patch generation.

From a capital perspective, Google prioritizes internal computing power and model resources to invest in the defense loop of Chrome, its core traffic entry point, motivated by the need to reduce systemic risks of large-scale vulnerabilities being exploited externally, while transforming the speed of security iteration into a product moat, shifting resources from traditional manual reviews to multi-agent workflows.

Similar cases can be seen in Microsoft's record number of fixes on Patch Tuesday and the early impact of automated fuzz testing tools on open-source software; currently, Chrome is transitioning from periodic major version fixes to high-frequency AI-driven continuous patches, moving from a passive response to proactive excessive discovery.

This fundamentally represents a technological substitution. AI liberates vulnerability discovery and remediation from human bottlenecks, creating a positive feedback loop of exponentially increasing discovery volume and forced patch frequency, leading capital to accelerate towards platforms that can simultaneously control offensive and defensive AI capabilities, while compressing the pricing power of traditional labor-intensive security models.

ABAB News · Cognitive Laws

AI discovery speed forces patch frequency
Defense efficiency determines product moat
Tool substitution precedes process reconstruction