Cybersecurity Investors Put $6.8B To Work In The Third Quarter, Mostly In Larger Rounds
For the third quarter of 2026, global cybersecurity- and privacy-focused startups pulled in a total of $6.8 billion, per Crunchbase data. That’s up about 50% from the prior quarter and tied for the highest quarterly tally in years.
Investors have allocated $6.8 billion towards cybersecurity firms in the third quarter of 2026, according to Crunchbase data, marking a significant increase of around 50% from the previous quarter and a high point in recent years. This surge in investment is driven by larger funding rounds rather than an increase in the number of rounds.
Cybersecurity funding primarily went to AI startups, with a focus on identity security. Notably, Keyfactor, an enterprise identity security provider, received the largest single investment of $1 billion in a July growth round led by Summit Partners. Keyfactor, founded in 2001, has primarily invested in AI-related ventures over the past decade.
Island, a Dallas-based startup, tied for second place with a $400 million September Series F led by Evolution Equity Partners. Island's services assist enterprises in monitoring and managing interactions between people and AI agents with applications and data, and it achieved a $6.4 billion post-money valuation. Cyera, a New York-based enterprise data security platform, also raised $400 million in September, driven by its AI agents focus, setting a $12 billion valuation.
Other acquisitions were made this quarter, including Visa's $2.4 billion purchase of BioCatch for its fraud detection capabilities and Cyera's acquisition of Oasis Security for around $1 billion. In the public sector, Aura completed a deal to acquire Australian company Qoria and rebrand itself as Aura. The positive funding trend in cybersecurity reflects concerns over the risks posed by advancing AI technology, but it indicates that investors remain optimistic about the future of cybersecurity startups.
Written by urgent.news from Crunchbase News's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.