Imagine two security analysts engaging in conversation about the intricacies of their work when one receives hundreds of vulnerability alerts; all scored high risk at seven or eight.
The exchange between our two analysts sheds light on the significance of context in cybersecurity.
The common vulnerability scoring system is frequently used to measure the probable severity of a vulnerability, reflected in a score on known vulnerabilities from low to severe.
It cannot provide the context to measure real risk or prioritize found threats accurately, leaving security teams grappling with a sea of vulnerabilities that may pose only minimal risk.
When assessing risks and vulnerabilities, context is our guiding light.
The importance of contextual information in cybersecurity cannot be overstated.
Now, imagine your vulnerability scanner as a trusty assistant, diligently searching for vulnerabilities and weaknesses in your systems.
That's where AI-driven context becomes our trusty sidekick, helping us unravel the mysteries beneath the surface.
The problem with legacy solutions has been the need for more vulnerability prioritization.
Security teams are presented with lists of vulnerabilities with no context to discern actual risk.
AI-driven vulnerability management offers the key to clarifying and streamlining this once-time-consuming process.
Generative AI and deep learning-based large language models leverage massively large data sets to discover, validate and recommend measures to mitigate vulnerabilities within the software business.
Many security companies are incorporating generative AI and LLMs that are grounded by verified data sets to combat software vulnerabilities.
AI-powered cybersecurity solutions use generative AI and LLM to analyze massive data sets in real-time to identify, prioritize, validate and make recommendations for mitigations with speed and effectiveness.
AI vulnerability management can scan and predict threat risks across thousands of attack vectors.
Crucial context-based prioritization of vulnerabilities is provided to enable more accurate risk scores.
Deploying the right AI-enabled vulnerability scanning and tools like automated penetration testing can make vulnerability identification, prioritization, and remediation fast, easy, and more accurate.
The only way to meet today's AI-driven threats head-on is to scale vulnerability exposure management through AI-driven cybersecurity.
Incorporating context into our cybersecurity efforts allows us to cut through the confusion, reduce false positives and focus on the genuine threats that demand our attention.
Context is our cybersecurity ally; together, we can navigate the ever-changing digital security landscape with speed, confidence and clarity.
This Cyber News was published on securityboulevard.com. Publication date: Tue, 09 Jan 2024 15:43:04 +0000