MIxmode Blog

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

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MixMode Guide: The Next Generation SOC Tool Stack – The Convergence of SIEM, NDR and NTA

In our latest MixMode Guide we discuss the convergence of legacy network security tools and explore how security teams can upgrade their SOC with the next generation of cybersecurity tools.

Redefining the Definition of “Baseline” in Cybersecurity

While many security solution providers promise to protect your network by establishing a baseline of your network behavior, the definition of “baseline” can vary widely.

Network Data: The Best Source for Actionable Data in Cybersecurity

With the right tool, your network data can now provide you with most valuable, actionable alerts in your security stack.


Deep Dive: How much time do security teams spend labeling with Supervised Learning?

By Christian Wiens | July 28, 2020

Many CISOs and SecOps teams were faced with a gut-wrenching choice: addressing the operational challenges of keeping workers connected, or shoring up vulnerabilities before hackers exploited them. Both options involved time-consuming, repetitive, manual work.

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Why a Platform With a Generative Baseline Matters

By Christian Wiens | July 23, 2020

MixMode creates a generative baseline. Unlike the historically-based baselines provided by add-on NTA solutions, a generative baseline is predictive, real-time, and accurate. MixMode provides anomaly detection and behavioral analytics and the ability to suppress false positives and surface true positives.

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Why The Future of Cybersecurity Needs Both Humans and AI Working Together

By Ana Mezic | July 21, 2020

A recent WhiteHat Security survey revealed that more than 70 percent of respondents cited AI-based tools as contributing to more efficiency. More than 55 percent of mundane tasks have been replaced by AI, freeing up analysts for other departmental tasks.

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Our Q2 Top Cybersecurity Insights

By Christian Wiens | July 16, 2020

Since we determine everything on data here at MixMode, we went into our website data to see which of our Q2 articles got the most traffic over the past few months. Not surprisingly, the majority of our top articles covered topics on the advancement of AI in cybersecurity and network traffic analysis (NTA).

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NTA and NDR: The Missing Piece

By Christian Wiens | July 14, 2020

Most SIEM vendors acknowledge the value of network traffic data for leading indicators of attacks, anomaly detection, and user behavior analysis as being far more useful than log data. Ironically, network traffic data is often expressly excluded from SIEM deployments, because the data ingest significantly increases the required data aggregation and storage costs typically 3-5x.

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The Problem with Relying on Log Data for Cybersecurity

By Christian Wiens | July 9, 2020

One of the most prevalent issues impacting the effectiveness of security teams who use SIEM as their primary means of threat detection and remediation is the fact that data logs are an attractive medium for modern hackers to exploit.

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The (Recent) History of Self-Supervised Learning

By Christian Wiens | July 7, 2020

Real unsupervised AI spots security issues sooner and predicts future behavior more accurately than older first- and second-wave solutions. Self-supervised AI technology draws on an understanding of the fundamental nature of the network where it lives, an understanding that isn’t possible with supervised-AI.

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Guide: The Next Generation SOC Tool Stack – The Convergence of SIEM, NDR and NTA

By Christian Wiens | June 30, 2020

Traditional security vendors offering solutions like SIEM (Security Information and Event Management) are overpromising on analytics while also requiring massive spend on basic log storage, incremental analytics, maintenance costs, and supporting resources.

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Redefining the Definition of “Baseline” in Cybersecurity

By Christian Wiens | June 25, 2020

While many security solution providers promise to protect your network by establishing a baseline of your network behavior, the definition of “baseline” can vary widely.

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MixMode CTO Responds to Self-Supervised AI Hopes

By Ana Mezic | June 23, 2020

Yann LeCun and Yoshua Bengio were recently interviewed by VentureBeat Magazine on the topics of self-supervised learning and human-level intelligence for AI. Our CTO Dr. Igor Mezic sat down with our team to discuss some of the most interesting pieces of the LeCun article, and offer a potential solution to a search for truly self-supervised …

MixMode CTO Responds to Self-Supervised AI Hopes Read More →

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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.