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Prioritize Cyber Riskby Attack Probability and Urgency

The National Vulnerabilities Database identifies over 3,000 new cyber vulnerabilities and exposures each month. How can your team prioritize cyber risk and focus your resources on the most pressing cyber threats? How do you determine which threats require immediate action and which can be scheduled for triage at a later date?

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MEET PATHFINDER

GET FOCUSED. REDUCE COSTS.
ACHIEVE BETTER SECURITY.

Prioritize vulnerabilities by attack probability, risk, and urgency.

  • Determine the real-world exploitation timeframe of vulnerabilities to clearly assess the cyber risk landscape.
  • Achieve a lower risk environment by expending resources where they matter most.

Use AI to predict when attackers will strike.

  • Use threat intelligence and data-backed time windows to plan vulnerability patching timelines.
  • Force your adversaries to spend increasing amounts of effort to achieve marginal outcomes.
  • Achieve a lower risk environment by expending resources where they matter most.

Increase the value of every dollar spent on cybersecurity.

  • Use vulnerability intelligence to assess critical applications, build smarter POAMs, and eliminate wasted resources.
  • Reduce the need for expensive incident response and triage and lower your cyber insurance costs.
  • Achieve a lower risk environment by expending resources where they matter most.

ENTER CARTOGRAPHER

Visualize your network with 躂圖AV Pathfinders first major expansion module.

Sprawling, complex networks are difficult to understand and visualize. Whenever organizations are merged, deployed, shut down, or absorbed, clusters and sites often exist outside of standard network structures.

躂圖AV Pathfinder Cartographer leverages AI to:

  • Produce an interactive visualization of your network, including a heat map that reveals the locations of high-threat vulnerabilities. This helps you understand the location of a compromise actual or predicted as well as likely attack paths through your network.
  • Generate patching and segmentation recommendations that you can implement or ignore based on your local knowledge of unusual use cases, allowing you to filter out recommendations that could cause problems.

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