Cynergy’s advanced Machine Learning models are contextualizing and rank vulnerabilities in a company’s systems and networks based on the level of risk, severity, and likelihood.
This process helps your organization to prioritize which vulnerabilities to address first, as it is often not possible or practical to address all vulnerabilities at once.
There are several different methods that can be used to prioritize vulnerabilities. At Cynergy, we have adopted the pragmatic approach which includes evaluating the potential impact and likelihood of each vulnerability being exploited. For example, a vulnerability that could allow an attacker to gain access to sensitive data or disrupt critical systems would be given a higher priority than a vulnerability that only affects a minor feature or system.
Other factors that Cynergy is taken into consideration when prioritizing vulnerabilities include the following:
- The availability of patches or fixes
- The ease of exploitation
- The level of exposure of the vulnerability (e.g., whether it is publicly known or has been exploited in the wild).
- Cynergy is also using industry-standard practices i.e., EPSS and CVSS in its prioritization algorithm
By prioritizing vulnerabilities, your teams can focus the resources on addressing the most serious threats first, while still addressing other vulnerabilities as time and resources allow. This helps elevate efficiency and reduction of security resource costs. Addressing the prioritized issues first will help your organization adequate protection from cyber-attacks and can continue to operate smoothly.