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What is Palo Alto Networks NGFW?

Our hardware solutions equipped with ML-Enhanced NGFW technology empower users to proactively address unidentified threats, achieve comprehensive visibility across all devices, including IoT, and reduce errors with automated policy recommendations. The VM-Series functions as the virtual equivalent of our ML-Enhanced NGFW, protecting your applications in both private and public cloud environments through efficient segmentation and robust threat prevention strategies. Concurrently, the CN-Series, specifically crafted for containerized settings, guarantees that complex network threats cannot spread across Kubernetes namespace boundaries, significantly bolstering security measures. Collectively, these advanced solutions offer a thorough defense framework tailored to meet the unique needs of various infrastructures, ensuring that organizations can adapt to evolving security challenges effectively. This multifaceted approach not only enhances protection but also simplifies management for IT teams.

What is Cryptomage?

Threat detection involves a meticulous analysis of each network packet and its data, which includes identifying and verifying network protocols to uncover both hidden and obscure ones. It utilizes machine learning methodologies that enable a forward-looking evaluation of traffic risk, employing scoring systems to quantify potential threats. The identification of network steganography plays a crucial role in detecting concealed traffic within the network, potentially revealing data breaches, espionage, and botnet activities. By applying specialized algorithms for detecting steganography, this approach effectively exposes various strategies used to hide information. In addition, a distinctive database filled with a wide range of known steganography techniques significantly boosts detection efficacy. Forensic analysis is employed to assess the ratio of security incidents in relation to their traffic origins, providing valuable insights. This also aids in isolating high-risk network traffic for targeted analysis based on specific threat levels, and storing the metadata from processed traffic in an extended format further streamlines the trend analysis process. Overall, this comprehensive strategy not only deepens the understanding of network security issues but also improves the responsiveness to new and evolving threats, ensuring that organizations remain vigilant and prepared.