Armadin Raises Record $190 Million to Combat AI-Driven Cyberattacks

Cybersecurity company Armadin raised a record $189.9 million, according to a Tuesday (March 10) press release.

The company’s combined seed and Series A funding round is said to be the largest such financing round in cybersecurity history and will help Armadin in its goal of combating “hyperattacks,” which are “sophisticated, multi-modal campaigns that move at machine-speed,” the release said.

To combat this, Armadin’s platform offers specialized artificial intelligence agents that employ “custom models in an agentic attacker swarm,” per the release. These agents continuously reason, plan and adapt like the fraudsters to give companies “decision-grade proof of what can actually be exploited.”

“The AI shift is changing cybersecurity more rapidly than any transition in history,” Armadin CEO Kevin Mandia said in the release. “In a world of machine-speed attacks, defense must become autonomous. You cannot have a human in the loop for every defense decision and expect to win. We are building the most formidable offense to give organizations the greatest defense. It’s important to national security.”

Mandia is the former CEO of cybersecurity firm Mandiant, which was acquired by Google in 2022 for $5.4 billion. Armadin’s founding team includes veterans of both companies.

The new funding round came as “offensive” AI models are rewriting the way companies deploy their defensive counterparts, PYMNTS reported last month. According to the World Economic Forum, 87% of organizations said AI-related vulnerabilities are increasing risk across their environments.

“The threat landscape has shifted from AI as a tool to AI as an operation embedded throughout the attack lifecycle,” PYMNTS added.

Meanwhile, Gartner projected that by next year, 17% of cyberattacks will employ generative AI, a sign that AI-driven techniques are shifting from experimentation to mainstream threat capability.

“The result is compounding scale and variability,” the report said. “Artificial intelligence systems can generate unique attack instances while pursuing the same objective, weakening signature-based detection models that rely on pattern repetition. When each payload or prompt sequence is slightly different, static defenses struggle to keep pace.”

There is also a rise of attacks using fraudulent AI assistants designed to impersonate legitimate tools and collect sensitive user information, the report said.

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