Employ industry-first prevention of zero-day threats with inline deep learning models that detect 96% of web-based Cobalt Strike and 90% of unknown injection attacks. Stop 48% more unknown command and control and 60% more zero-day exploits than traditional IPS solutions.
The only solution to block unknown C2 attacks and exploit attempts in real time using Advanced Threat Prevention’s industry-first, purpose-built inline deep learning models.
Safeguard your network from known threats, such as exploits, malware, spyware, and command and control attacks, with market-leading, researcher-grade signatures that don’t compromise performance.
Advanced Threat Prevention blocks threats at both the network and application layers, including port scans, buffer overflows and remote code execution, with a low tolerance for false positives.
Protect against the most recent and relevant malware with payload signatures, not hash, to block known and future variants of malware, and receive the latest security updates from Advanced WildFire® in seconds.
Leverage User-ID™, App-ID™ and Device-ID™ technology on our ML-Powered NGFWs to add context to all traffic on all ports so you never lose sight of a threat, regardless of the techniques used.
Add to your threat coverage with flexible Snort and Suricata rule conversion for customized protections.
Advanced Threat Prevention protects your network by providing multiple layers of prevention during each phase of an attack while leveraging deep and machine learning models to block evasive and unknown C2, and stop zero-day exploit attempts inline.
Protect your network against new and existing threats without impacting performance.
Chat with our network security experts to learn how you can get real-time, inline protection against sophisticated threats with Advanced Threat Prevention.
