MIxmode Blog

MixMode Product Updates, Stories on Cybersecurity, AI, and Everything in Between.

Featured Content

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.

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.

The Case Against Using a Frankenstein Cybersecurity Platform

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.

ALL BLOGS

How Data Normalization in Cybersecurity Impacts Regulatory Compliance

By Christian Wiens | October 6, 2020

Complying with privacy regulations requires all organizations to have access to data on demand, wherever it lives on a network. With the unfathomable amount of data managed by most organizations operating in the finance space today, it can become a significant challenge to locate specific data across legacy systems and networks with countless connections online and off.

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Webinar: The Failed Promises of SIEM – What’s Next For Cybersecurity

By Christian Wiens | September 29, 2020

The Security Operations Center (SOC) of today is fundamentally flawed. Currently enterprise cybersecurity spend is higher than ever, but despite multi-million dollar cybersecurity investments, organizations remain vulnerable to attacks. One of the major reasons for this is legacy SIEM deployments. More spend does not equal more security.

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3 Reasons Why a Rule-Based Cybersecurity Platform Will Always Fail

By Ana Mezic | September 24, 2020

When it comes to advancements in cybersecurity, rule-based systems are holding the industry back. Relying on humans to constantly input and label rules in order to detect and stay ahead of threats is a bottleneck process that is setting security teams up for failure, especially with tools like SIEM, NDR, and NTA.

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Why Data Overload Happens and Why It Is a Problem for Cybersecurity Teams

By Christian Wiens | September 17, 2020

Handling and managing data today has become unwieldy for IT teams on multiple fronts, but the security impact is especially troubling.

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Why SIEM Has Failed the Cybersecurity Industry

By Ana Mezic | September 15, 2020

The time required for data processing, transition, aggregation, and the normalization does not allow real-time threat detection using today’s SIEM solutions. The only beneficiary of security through log aggregation is the SIEM vendor.

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Data Overload Problem: Data Normalization Strategies Are Expensive

By Christian Wiens | September 9, 2020

Financial institutions spend five to ten million dollars each year managing data. A recent Computer Services Inc (CSI) study reveals that most banks expect to spend up to 40 percent of their budgets on regulatory compliance cybersecurity, often adopting expensive data normalization strategies.

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What is Predictive AI and How is it Being Used in Cybersecurity?

By Ana Mezic | September 3, 2020

The predictive AI field of machine learning collects, analyzes, and tests data to predict future possibilities. AI’s neurological network is patterned on the human brain. But AI works on a scale that goes far beyond what is humanly possible. The top uses for predictive AI technologies to protect sensitive data and systems are in network detection and response (NDR), threat detection, and cybercrime prevention.

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Whitepaper: The Data Overload Problem in Cybersecurity

By Christian Wiens | September 1, 2020

The very nature of data is its infinite capacity for growth. For security teams at large, highly integrated and complex enterprises like financial services institutions, that growth can quickly become unwieldy when the approach is to store, normalize and prepare all of this data in order to extract value.

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Magnify Podcast: Discussing the New Normal with AI Based Cybersecurity Specialists, MixMode

By Christian Wiens | August 27, 2020

Geoff Coulehan, MixMode’s Head of Strategic Alliances, joined Secrutiny’s “Magnify Podcast,” to discuss the priorities CISOs should focus on to better protect their now-remote team of employees.

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MixMode Platform Update: Support for Google Cloud

By Chris Hinshaw | August 20, 2020

MixMode is proud to release our platform sensor for Google Cloud! With this capability, customers can now monitor their Google Cloud infrastructure for security anomalies and zero-day attacks, using the same industry-recognized MixMode platform enterprises already use for on-premise security monitoring, Amazon Web Services monitoring, and Microsoft Azure monitoring.

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About 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.