Last month, we were faced with another attack. It’s funny, isn’t it? The only thing that we are assured of these days is that an attack will happen. To be truthful, last month’s logjam vulnerability was a bit more of an issue than most. I was talking about the attack with one of our larger European customers and they supported a position that I have had since I started with Plixer over 15 years ago. In a critical situation, similar to the log4j attack, leveraging contextual metadata is the most efficient way to contain the incident. Here are a few reasons why metadata is the better choice for your visibility needs.
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Network Detection and Response as an investment: How to calculate the value
Posted on - by Jeff Lindholm
This is the final post in a 4-part series of articles by Plixer’s CEO, Jeff Lindholm. Be sure to check out part 1, How to use NDR as a radar system for your network, part 2, Why network metadata analysis is the best initial action to inform security teams, and part 3, Containing a cyberattack: How NDR strengthens your response.
In this blog series, I’ve discussed how Network Detection and Response (NDR) solutions play a critical role in the fight against cyberattacks through detection, analysis, and containment of threats within your network. Security Operations teams rely on tools like NDR to identify and isolate nefarious behavior. Acting as a radar system for your network, NDR systems provide early detection of threats and work with your existing infrastructure to isolate and neutralize them. Still, with the increasing demand on your budget, it can be challenging to figure out how to pay for another security tool.
Read moreContaining a cyberattack: How NDR strengthens your response
Posted on - by Jeff Lindholm
This is part 3 in a 4-part series of articles by Plixer’s CEO, Jeff Lindholm. Be sure to check out part 1, How to use NDR as a radar system for your network and part 2, Why network metadata analysis is the best initial action to inform security teams.
In this blog series, we’ve been talking about how to use NDR to stop cyberattacks. But no matter what tools you use to detect nefarious behavior in your network, the end goal is always the same: to stop it quickly and comprehensively.
Read moreWhy network metadata analysis is the best initial action to inform security teams
Posted on - by Jeff Lindholm
This is part 2 in a 4-part series of articles by Plixer’s CEO, Jeff Lindholm. Be sure to check out part 1, How to use NDR as a radar system for your network.
In my last blog, I wrote about how the metadata collected by the multitude of behavior sensors already deployed across your network can provide the best early warning system you can find. Much like a radar system for on-water navigation, your network metadata is the fastest way to gain a sense of the potential dangers around you. But can it really provide the context you need to understand your network traffic comprehensively?
Read moreHow to use NDR as a radar system for your network
Posted on - by Jeff Lindholm
This is the first in a 4-part series of articles by Plixer’s CEO, Jeff Lindholm.
In the warmer months here in New England, you can often find me on my small boat cruising around Boston harbor and the outer islands. As a safety-focused boater, I rely on my radar system to detect the many objects around me—everything from other watercraft, buoys, landmasses, even uncharted hazards (the nautical version of zero-day threats). My radar is my best early detection system, alerting me to all possible threats.
Read moreThe 7 best Network Detection and Response use cases
Posted on - by Adam Boeckmann
Hallmarked by the application of machine learning to network metadata, Network Detection and Response leverages advanced intelligence and integrations with response-capable solutions such as NAC and SIEM to provide incredible visibility into an organization’s network traffic. This is a stark contrast to the traditional approach of leveraging thresholds and pre-defined traffic patterns to automate network alerts. While this approach works just fine for detecting certain threats—think DDoS or SYN scans as an example—there is just so much more we can do confidently with machine learning. Let’s explore some of the more popular Network Detection and Response use cases.
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