Cybersecurity startup Empirical Security has closed a $25 million Series A funding round led by Brightmind Partners, bringing its total capital raised to $32 million, as it positions itself at the frontline of a new category of threat: AI-accelerated cyber exposures. The company builds data-driven models that continuously monitor over 18,000 known exploited CVEs (Common Vulnerabilities and Exposures) to help enterprises prioritize, remediate, and summarize cybersecurity findings before attackers can weaponize them.
The raise reflects a broader shift in the cybersecurity venture market, where investors are increasingly backing platforms that use AI not just to detect threats but to predict and neutralize the exponentially growing attack surface created by AI itself. AI tools have lowered the barrier to entry for cybercriminals, enabling faster reconnaissance, more convincing phishing, and automated exploitation of known vulnerabilities. Empirical Security's approach directly counters that dynamic by applying machine learning to vulnerability intelligence, allowing security teams to focus resources on the highest-risk exposures rather than drowning in alerts.
The round signals confidence that AI-native security platforms will be essential infrastructure as the arms race between attackers and defenders intensifies.