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SIEM

Why Traditional Cybersecurity Tools Cannot Defend Against Zero-Day and No Signature Attacks

Blog, NTA, Ransomware, SIEM, UEBA, XDR, Zero Day Attacks / By

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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Incremental Stacking of Correlative Analysis Platforms Will Ultimately Prove Ineffective and Costly

Blog, CISO, Network Baselines, Network Security, Predictive AI, Self-Supervised AI, SIEM, SOC, Unsupervised AI / By

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.

Incremental Stacking of Correlative Analysis Platforms Will Ultimately Prove Ineffective and Costly Read More →

A Modern SOC Should Not Be Entirely Dependent On Human Operators and Their Personal Experience

Blog, False Positives, SIEM, SOC, Third-Wave AI, Zero Day Attacks / By

A modern SOC should not be entirely dependent on human operators and their personal experience. The issue has been a foundational problem with not only the methodologies used by SOCs for the past 15 to 20 years, but it should be questioned whether the problem is actually compounded by the technology itself.

A Modern SOC Should Not Be Entirely Dependent On Human Operators and Their Personal Experience Read More →

Maximize ROI with Greater Efficacy Using Unsupervised AI

Blog, Case Study, Data Storage Cost, Log Data, Network Security, SIEM, SOC, Unsupervised AI / By

Within the first 24 hours after deployment, MixMode had enabled the government entity to regain control over the security environment and network data infrastructure. No longer limited to log data analysis, they were able to identify and address real-time threats as well as network and operational configuration challenges.

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How Self-Supervised AI Tackles Ambiguity in Network Security

Blog, Context-Aware AI, Log Data, Network Baselines, Network Detection and Response, Network Security, Predictive AI, Self-Supervised AI, SIEM, Third-Wave AI / By

Cybersecurity vendors promise the moon when it comes to AI. As the recent TechRepublic article, “Why cybersecurity tools fail when it comes to ambiguity,” makes clear, often, these promises fail short in real world network environments.

How Self-Supervised AI Tackles Ambiguity in Network Security Read More →

2021: The Year SOCs Embrace Cybersecurity Convergence

Blog, Network Security, Predictive AI, SIEM, SOAR, SOC, Third-Wave AI, Threat Detection / By

Staying on top of cybersecurity risk can feel like a losing battle in today’s modern, hyperconnected reality. The influx of IoT devices and increased reliance of BYOD devices has created a diverse, complex threatscape rife with overlapping vulnerabilities across physical and cyber assets.

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Our Top 2020 Cybersecurity Insights

Blog, MixMode News, Network Baselines, Network Detection and Response, Network Security, Predictive AI, Self-Supervised AI, SIEM, SOC, Third-Wave AI, Webinar, Whitepaper / By

The transition from office to remote environments was abrupt and one of the most defining moments that the cybersecurity industry and professionals faced in 2020. We wrote about the top issues CISOs were facing throughout the year but also doubled down on sharing insights about the evolution of next-generation SOCs, the failure of SIEM platforms as organizations are experiencing them today, and how self-supervised AI fits into the equation.

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Russian Hack of U.S. Federal Agencies Shine Spotlight on SIEM Failures in Cybersecurity

Adversarial AI, Blog, Data Breach, Network Baselines, Network Detection and Response, Network Security, Network Traffic Analysis, Predictive AI, Self-Supervised AI, SIEM, Third-Wave AI, Threat Detection / By

In what the New York Times is calling, “One of the most sophisticated and perhaps largest hacks in more than five years,” malicious adversaries acting on behalf of a foreign government, likely Russian, broke into the email systems of multiple U.S. Federal agencies including the Treasury and Commerce Departments.

Russian Hack of U.S. Federal Agencies Shine Spotlight on SIEM Failures in Cybersecurity Read More →

MixMode in the Real World: Customers Turn to MixMode Frustrated and in Search of a Viable SIEM Alternative

Blog, SIEM, SOC, Threat Detection, Use Case / By

SIEM has failed to meet the needs of enterprises in the modern threatscape. One huge reason for this is that over time, most organizations will come to the sad realization that they will never achieve a full enterprise deployment of their SIEM. By its very nature, SIEM is always “in process.” It’s not unusual for an organization to have an SIEM in process for a full decade.

MixMode in the Real World: Customers Turn to MixMode Frustrated and in Search of a Viable SIEM Alternative Read More →

Featured Use Case: Why a Large US Utility Company Turned to MixMode to Address Utility Grid Vulnerabilities

Blog, Case Study, Network Security, SIEM, SOC / By

A large utility company approached MixMode with the following scenario: The enterprise SOC was utilizing a shared SIEM application that was being utilized by several stakeholders: the networking team, the SCADA team, the dev-ops team, the compliance team and cybersecurity teams for “basic search and investigation of log files to meet regulatory compliance requirements”.

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How Vendors Capitalize on SIEM’s Fundamental Flaws

Blog, SIEM, SOC, Whitepaper / By

Because the fundamental nature of SIEM requires infinite amounts of data, security teams are forced to constantly wrangle their network data and faced with an unmanageable number of false positive alerts. This means they have to devise efficient ways to collect, organize and store data, resulting in an incredible investment in human and financial resources.

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The Case Against Using a Frankenstein Cybersecurity Platform

Blog, Network Baselines, Network Detection and Response, Network Security, Network Traffic Analysis, Predictive AI, Self-Supervised AI, SIEM, SOC, Unsupervised AI / By

The cybersecurity market has, simply put, been cobbled together. A tangled web of non-integrated systems and alerts from siloed systems. Enterprises are now being forced to utilize a “Frankenstein” of stitched together tools to create a platform that might cover their security bases.

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Improving on the Typical SIEM Model

Blog, Network Detection and Response, Network Traffic Analysis, SIEM, SOC / By

Despite its inherent flaws, today’s SIEM software solutions still shine when it comes to searching and investigating log data. One effective, comprehensive approach to network security pairs the best parts of SIEM with modern, AI-driven predictive analysis tools. Alternatively, organizations can replace their outdated SIEM with a modern single platform self-learning AI solution.

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