Palo Alto has boosted this effort in recent years with the integration of precision artificial intelligence that includes machine learning and deep learning techniques, in addition to generative AI tools.
“Our strategy is to ensure that the time to detect an attack and the time to resolve it (if it has occurred) are zero; currently, the average we manage, which is a great advantage over our competitors, is 10 seconds to detect the attack and one minute to resolve it,” Botifoll says.
A global database to deal with threats
For Botifoll, one of the great differentials of Palo Alto is the large amount of data it handles, thanks, he stresses, to the activity it carries out with more than 85,000 clients (including 85 of the Fortune 100 companies) and the work of its emergency unit (Unit 42) “which also responds to calls from organizations that are not our clients but request our services in situations of relevant security breaches.”
“Our telemetry is able to analyze and understand polymorphic attacks. This continuous database we have is also very important for our artificial intelligence to be even more effective so that we can prevent an attack before it appears,” he adds.
The precision AI with which the firm works, Botifoll says, “allows us to act in real time and with automated processes that reduce errors, because it is a reality that humans make more mistakes than machines. In this era of massive attacks [Palo Alto detects 2.3 million net new attacks a day, up from 1.6 million last year], if an organization doesn’t have automated incident management, it has a problem.” In addition, he says, “cybercriminals are also using AI to generate malicious attacks, so you have to be well prepared.”
Although many cybersecurity companies are already adopting a platform strategy, in response to their customers’ demands to simplify the difficult management of multiple cybersecurity tools, Botifoll stresses that Palo Alto was a “pioneer” in this approach and is the “only one” that covers the entire cybersecurity lifecycle.
