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HomeMCUFeedly AI understands vulnerability threats – Feedly Blog

Feedly AI understands vulnerability threats – Feedly Blog

Feedly AI understands vulnerability threats – Feedly Blog

Do you need to keep up with the latest vulnerabilities and threats but do not have the time to read all your security feeds? We can help.

In 2018, fifteen thousand vulnerabilities were discovered, the number of exploits doubled and more than four security articles were published every minute. Keeping up with all these trends can be time-consuming and overwhelming.

This is a problem we are very passionate about and have been researching with two of the largest security teams in Silicon Valley.

Today, we are excited to announce a new AI Model called Security Threats.

We have been teaching Feedly AI to read security articles and find or assess the severity of the software vulnerabilities they mention so that it can help you focus your attention on the most critical threats in your feeds first.

Here is a demo!

Let’s look at how you can train your Feedly AI to prioritize articles mentioning critical vulnerabilities related to Microsoft, WordPress, or Docker.

Cut through the noise

Feedly AI reads and prioritizes the most critical threats in your feeds

Feedly AI continuously reads your feeds and short-lists the most critical vulnerabilities in the priority tab.

For example, you might have a cybersecurity feed connected to niche security experts, vulnerability databases, keyword alerts, etc. with thousands of new articles per month.

You can train Feedly AI to read those 1,000+ articles and prioritize the 30 or so referencing high severity threats (CVSS > 8) and related to vendors you care about (Microsoft, WordPress, Docker in the example above).

Feedly AI’s new Security Threat Models

You’re in control

Feedly AI is not an opaque recommendation engine. Instead, Feedly AI has a set of skills that gives you control over defining what information is important to you.

The new Security Threat skill allows Feedly AI to read an article, lookup CVE, CVSS, and exploit information from multiple open source databases and determine how critical a vulnerability is.

The new Security Threat skill also includes a sophisticated machine learning model that allows Feedly AI to assess the severity of a threat based on the vocabulary used to describe the software vulnerability. This is particularly useful for zero-day vulnerabilities which might not have a CVE or CVSS.

Training Feedly AI to prioritize vulnerabilities is very simple.

Creating a Feedly AI cybersecurity model

The first layer of the model captures the severity threshold. High means CVSS > 8 or CVSS > 5 but with an exploit.

The second layer of the model captures the list of vendors.

Control and transparency are core Feedly AI design principles.

All the articles prioritized by Feedly AI have a green priority marker. Clicking on that marker offers an explanation of why the article was prioritized and the opportunity to refine, pause or remove that priority.

Full control and transparency

When an article is related to a CVE, you can also click on that CVE to get additional information about the vulnerability: description, CVSS score, exploits, patches, etc.

Quick access to CVE information

Continuously learning and getting smarter

Feedly AI learns from its mistakes. When a recommendation is wrong, you can use the “Less-Like-This” down arrow button to correct Feedly AI.

Feedly AI learns from Less Like This feedback

You can let Feedly AI know that it misclassified a vulnerability, miscalculated the severity, or misidentified a vendor.

Feedly AI learns from your feedback and gets continuously smarter.

Streamline your open-source intelligence

We are excited to see many security teams declutter their feeds and dig deeper into the vulnerabilities that matter to them. Sign up today and discover what Feedly for Cybersecurity can do for you!

If you are interested in learning more about Feedly AI’s roadmap, you can join the Feedly Community Slack. 2020 will be a thrilling year with new skills and bold experiments!

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