A New Approach to Preventing Evasive Threats

As attackers continue to evolve their tactics, Palo Alto Networks has evolved its machine learning capabilities with the introduction of inline deep learning. While signature-based detection is still critical to preventing known threats, addressing these newer, more sophisticated techniques requires an innovative approach.

“Requirements for Preventing Evasive Threats,” a new white paper by leading security analyst ESG, offers valuable insights that address these key concerns.

In it, you’ll learn how these capabilities:

  • Help prevent unknown command-and-control traffic.
  • Block attacks from tools such as Cobalt Strike and detect attacks that evade traditional URL databases and web crawlers.
  • Ensure attackers cannot use DNS as an avenue of attack.

Access ESG’s insights on why it’s time for organizations to consider alternatives from signature-based detection and explore inline deep learning to deliver advanced protection against evasive threats.

Palo Alto Networks

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