Partners With Quad9 To Provide Predictive DNS Cybersecurity Protection Partners With Quad9 To Provide Predictive DNS Cybersecurity Protection-01 and Quad9 today announced their partnership to augment protective DNS with PreCrime cybersecurity protection. The integration of and Quad9 generates hundreds of thousands of new and unique indicators of future cyber threats, enabling their customers to be protected by cyber attacks before they even start.

The proof was in the pudding in mid-December 2021 when Quad9 blocked more than 365 million hits to a single known malicious domain. At its peak, the attack produced 94,000 unique resolutions per minute for over 24 hours. predicted the malicious domain in early November 2021 and shared it with Quad9 a month before the attack.

”We’re excited to add to the Quad9 threat-intelligence portfolio and are impressed with the significant ‘win’ that was visible so soon after our deployment of their threat intelligence feed,” says Danielle Deibler, Director of Threat Intelligence for Quad9. “Each and every one of these threat blocking events saves a user from being harmed, and we’re pleased to be able to offer the benefits of’s predictive threat technology to everyone using our free service.”

Also Read: Three Ways to Achieve a Seamless Cybersecurity Posture brings an innovative approach to threat intelligence to the Quad9 network by leveraging the predictive power of PreCrime, their proprietary AI engine.’s PreCrime Network brings sophisticated predictive capabilities to avoid domain-based attacks by offering forecasting of malicious attack vectors from six hours to multiple weeks in advance of attacks. Anticipation and better analytical tools can make a difference in fighting domain names abuse, where time and accuracy are key factors.

Luigi Lenguito, founder and CEO of said, “I am a longtime fan and use Quad9 to protect my family, so it is an honor to see our technology deployed in their unique infrastructure, knowing the impact it will have on so many people.”

In exchange for the predictive prevention for Quad9, will benefit from the telemetry data on the frequency of filtering of their IOCs. This information will assist in understanding criminal activity dynamics and will expand’s machine learning model.

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