There was a recent LinkedIn post that was interesting. It was a short demonstration video of an image recognition and temperature scanning technology designed to screen people for COVID-19. Those wishing to enter a building paused for a few seconds, and an automated system confirmed they were wearing a mask and they weren’t feverish. When those two criteria were satisfied, they were granted entry. No human with a hand-held thermometer in a hazmat suit was required. The system was a perfect example of how technology - including machine learning - can be deployed to address contemporary challenges to minimize cost and health risk.
That contrasted starkly with multiple posts that read like they were written a decade ago, posts that laboriously detailed the nuances of newly-introduced software vulnerabilities. One post advertised an upcoming webinar that would shed light on Microsoft’s Patch Tuesday’s list of new vulnerabilities. Another linked to a blog where a large vulnerability management vendor discussed a recent collection of a technology’s appliance patches. Yet another fanned the hype flame for a just-discovered critical vulnerability that the manufacturer implored users to patch “as soon as possible.”
More than 20,000 new vulnerabilities were disclosed in 2019. Think about that for a second: 20,000 new vulnerabilities, on top of the hundreds of thousands published in years prior and still largely unpatched on countless networks. Does anyone believe it’s a good use of time to attempt to understand the nuances of even a fraction of 2019’s 20,000 vulnerabilities?
When you hire an electrician to wire your house, you don’t study wiring codes. When you visit a restaurant, you don’t learn the preparation details of the dish you’re ordering. If you had to invest that kin ..
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