MIxmode Blog
MixMode Product Updates, Stories on Cybersecurity, AI, and Everything in Between.
Featured Content
SOAR - The Acknowledgement that all of your cybersecurity platforms have failed
Is having 5 disparate cybersecurity platforms truly helping make your enterprise more secure? In this whitepaper we explain why it's not and why we believe the adoption of SOAR is just an admission that all of your other cybersecurity platforms aren't doing their job.
Featured Use Case: Why a Large Government Entity Replaced Their SIEM with MixMode
Despite a three-year SIEM deployment and a two-year UBA deployment, government personnel needed an alternative to better detect and manage threats in real-time. They turned to MixMode.
MixMode Guide: The Failed Promises of SIEM
In this whitepaper we'll discuss the ways in which SIEM has failed to deliver on promises made to the cybersecurity industry and why cyber teams must instead turn to a next-gen platform powered by unsupervised AI.
ALL BLOGS
It’s evident that while organizations are spending more and more on legacy cybersecurity solutions, these platforms are not holding up their end of the deal and are not able to proactively defend in a modern, non-signature attack threatscape.
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In our upcoming webinar on Tuesday, May 18th, “Why Your Legacy Cyber Platforms Can’t Defend Against Modern Day Attacks,” CEO of RAVENii, Jeff Shipley joins MixMode Head of Sales and Alliances Geoff Coulehan to uncover why the cybersecurity industry is failing to deliver on its promises.
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Unfortunately, the majority of cybersecurity solutions available today rely on outdated applications for AI. So-called first- and second-wave AI solutions don’t cut it, but few vendors have the technical capabilities and know-how to apply cutting edge, third-wave AI to their platforms.
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Organizations are exclusively depending on selective information forwarded to the SIEM. The information that inevitably exists outside the system of record — information relevant for zero-day attacks — is ignored.
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Managing a relatively small, stable data store is one thing, but dynamic companies face immense challenges when those circumstances change. Data growth can become unwieldy to safeguard when it has to be carefully prepared through a series of time-consuming, manual processes before the security software can evaluate it.
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The following is an excerpt from our recent whitepaper, “Why Traditional Cybersecurity Tools Cannot Defend Against Zero-Day and No Signature Attacks,” in which we dive into how traditional cybersecurity tools work, why this fundamentally limits them from being able to detect zero-day or previously unknown attacks, why the industry standard for breach detection is around …
The Aggregation Model is Falling Short Read More →
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In the imperfect, real world, where SOC teams actually live, the SIEM log-based approach is fundamentally flawed. In fact, it tends to add more challenge to the workday for SOC teams, not less.
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In our newest whitepaper, “Why Traditional Cybersecurity Tools Cannot Defend Against Zero-Day and No Signature Attacks,” we dive into how traditional cybersecurity tools work, why this fundamentally limits them from being able to detect zero-day or previously unknown attacks, why the industry standard for breach detection is around six to eight months and how modern, contextually-aware AI overcomes the limitations of traditional cybersecurity solutions.
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What does Bitcoin’s energy consumption problem have to do with AI? At a fundamental level, it turns out, some AI applications require similarly massive amounts of computing energy to function.
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On the surface, an “incremental stacking” approach to correlative analysis platforms like SIEM, XDR and UEBA is logical. Organizations can overcome some of the inherent limitations present in their security solutions by adding a network traffic analysis (NTA), for example. Industry analysts have been touting this approach for some time now as necessary for full coverage enterprise security.
Read MoreAbout MixMode
MixMode is the first to bring a third-wave, context-aware AI approach that automatically learns and adapts to dynamically changing environments. MixMode’s monitoring platform, PacketSled, better understands network behavior as it adapts to baseline changes and enables both misuse detection and anomaly detection, as well as predictive maintenance. Used by enterprises and MSSPs for real-time network analysis, threat hunting and incident response, the platform leverages continuous stream monitoring and retrospection to provide network forensics and security analytics. Security teams can integrate PacketSled into their orchestration engine, SIEM, or use PacketSled independently to dramatically reduce false positive alerts and the resources required to respond to persistent threats, malware, insider attacks and nation state espionage efforts.
The company has been named an innovator in leading publications and by security analysts, including SC Magazine, earning a finalist award in 2018 and 2019 for "Best Computer Forensic Solution.” Based in Santa Barbara, with offices in San Diego, the company is backed by Keshif Ventures and Blu Venture Investors. For case studies, continuous product updates and industry news, please visit us at www.mixmode.ai.