Mixmode Blog
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Forbes Technology Council: Why Large Language Models (LLMs) Alone Won’t Save Cybersecurity
The star of the moment is Large Language Models (aka LLMs), the foundational model that powers ChatGPT. There are plenty of documented examples of truly impressive feats built on this technology: writing reports or outputting code in seconds. At its core, LLMs basically ingest A LOT of text (e.g., think Internet) as a corpus of training data and rely on human feedback in a type of supervised training called reinforcement learning.
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eBook: The Inefficiencies of Legacy Tools – Why SIEMs Alone Are Ineffective At Detecting Advanced Attacks
Relying solely on legacy Security Information and Event Management (SIEM) technology is no longer sufficient to protect enterprise organizations from the rising amount of modern, ai-developed, sophisticated cyberattacks. In our newest eBook, we examine the limitations of SIEMs and emphasize the need for an AI-driven dynamic threat detection and response platform.
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Unleashing the Power of Self-Supervised AI: Insights from 451 Research Report on MixMode’s Dynamic Threat Detection and Response
In an era where cyber threats are becoming increasingly sophisticated, it is crucial for organizations to stay ahead of attacks. By leveraging the power of self-supervised AI, MixMode offers a game-changing solution that can revolutionize threat detection and response capabilities.
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Verizon’s Annual Data Breach Incident Report (DBIR) Shines Spotlight on Ransomware Trends & Insider Threats
New research from Verizon reveals that ransomware is responsible for a sizable percentage of all recorded security incidents. Despite the alarming statistics raised in the report, the tech giant warns, we’re likely to see continued growth in the number of ransomware attacks against organizations.
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Aligning an Organization’s Attack Surface to Detection Surface is Key to Adversary Defense in Today’s Cloud Era
With the Cloud Era, the IT asset estate has expanded, and there is a diverse set of attack surfaces to defend. The term “attack surface” describes the growing IT asset estate, but there is no parallel term to describe where we can detect or respond to attacker activity.
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Detecting Threats in AWS with MixMode AI
As organizations increasingly operate within a hybrid on-premises and cloud environment, the need for advanced threat detection mechanisms becomes vital. Today I explore how The MixMode Platform leverages AWS CloudTrail and VPC flow logs to detect threats and safeguard your AWS environment.
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Top 5 Takeaways from the CISA 2023-2025 Strategic Plan That the Cybersecurity Community Should Know About
CISA identifies goals for the strategy as spearheading “the national effort to ensure the defense and resilience of cyberspace,” helping partners protect critical infrastructure, and supporting stronger “whole-of-nation operational collaboration and information sharing.” The strategy also outlines internal CISA goals focused on unification within the agency.
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How to Detect PowerDrop Command & Control Malware
MixMode Sales Engineer, Josh Snow, explores a real-time threat detection use case involving The MixMode Platform and its ability to identify PowerDrop, a malicious Powershell script that has been specifically targeting the aerospace industry and shows how MixMode’s Third Wave AI detects PowerDrop and gain insights into what this threat entails.
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Utilizing Generative AI Effectively in Cybersecurity
Generative AI tools have the potential to enhance various aspects of cybersecurity, from data augmentation and malware detection to anomaly detection and security testing. By harnessing the power of Generative AI, organizations can strengthen their defenses, improve threat detection capabilities, and enhance their overall cybersecurity posture.
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