MIxmode Blog

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

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

By Christian Wiens | December 3, 2020

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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Recent Ransomware Attacks on U.S. Hospitals Highlight the Inefficiency of Rules-Based Cybersecurity Solutions

By Christian Wiens | November 19, 2020

A number of recent high profile ransomware attacks on U.S. hospitals have demonstrated the urgency for organizations, municipalities, and critical services to take a proactive approach to protecting networks with a predictive AI solution.

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Featured Use Case: Why a Large Government Entity Replaced Their SIEM with MixMode

By Christian Wiens | November 17, 2020

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, as well as an improved platform for gathering comprehensive data.

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Stop Patching Leaks in Your Cybersecurity Boat: A Streamlined Cybersecurity AI Solution to Adversarial Attacks

By Ana Mezic | November 12, 2020

At MixMode our one algorithm is capable of catching any anomaly that may appear on the network. In contrast, other security programs rely on a reactive method of patching and constantly adding to their algorithms each time a hack occurs so that the network learns what to look out for.

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How Vendors Capitalize on SIEM’s Fundamental Flaws

By Christian Wiens | November 5, 2020

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

By Ana Mezic | October 29, 2020

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

By Christian Wiens | October 27, 2020

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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Webinar Recap: The Failed Promises of SIEM

By Christian Wiens | October 15, 2020

MixMode teamed up with Ravenii to host a webinar focused on the history and evolution of SIEM platforms, their ideal role in a SOC today, and how they fall short as a threat detection tool in today’s modern cybersecurity environment.

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The Evolution of SIEM

By Christian Wiens | October 13, 2020

It should be noted that SIEM platforms are exceptionally effective at what they initially were intended for: providing enterprise teams with a central repository of log information that would allow them to conduct search and investigation activities against machine-generated data. If this was all an enterprise cybersecurity team needed in 2020 to thwart attacks and stop bad actors from infiltrating their systems, SIEM would truly be the cybersecurity silver bullet that it claims to be.

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Whitepaper: The Failed Promises of SIEM

By Geoffrey Coulehan | October 8, 2020

The fundamental SIEM flaws lie in the platform’s need for continual adjustment, endless data stores, and a tendency to create an overwhelming number of false positives. When organizations instead turn to a next-generation cybersecurity solution, which predicts behavior with an unsupervised (zero tuning) system, they are poised to save on both financial and human resources.

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About MixMode

MixMode is a no-rules Cybersecurity platform, serving large enterprises with big data environments across a variety of industries. MixMode delivers a patented, self-learning platform that acts as the Intelligence Layer℠ to detect both known and unknown attacks, including novel attacks designed to bypass legacy cyber defenses. This is accomplished in real-time, across any cloud or on-premise data stream. Trusted by global entities in banking, public utilities and government sectors, industry cyber leaders rely on MixMode to protect their most critical assets. The platform dramatically improves the efficiency of SOC teams’ previously burdened with writing and tuning rules and manually searching for attacks. The MixMode platform can be deployed remotely, with no appliances, in under an hour with business outcomes evident within days. Backed by PSG and Entrada Ventures, the company is headquartered in Santa Barbara, CA. Learn more at www.mixmode.ai.