It’s evident that while organizations are spending more and more on legacy cybersecurity solutions, these platforms are not holding up their end of the deal and are not able to proactively defend in a modern, non-signature attack threatscape.
In our upcoming webinar on Tuesday, May 18th, “Why Your Legacy Cyber Platforms Can’t Defend Against Modern Day Attacks,” CEO of RAVENii, Jeff Shipley joins MixMode Head of Sales and Alliances Geoff Coulehan to uncover why the cybersecurity industry is failing to deliver on its promises.
Unfortunately, the majority of cybersecurity solutions available today rely on outdated applications for AI. So-called first- and second-wave AI solutions don’t cut it, but few vendors have the technical capabilities and know-how to apply cutting edge, third-wave AI to their platforms.
Organizations are exclusively depending on selective information forwarded to the SIEM. The information that inevitably exists outside the system of record — information relevant for zero-day attacks — is ignored.
Managing a relatively small, stable data store is one thing, but dynamic companies face immense challenges when those circumstances change. Data growth can become unwieldy to safeguard when it has to be carefully prepared through a series of time-consuming, manual processes before the security software can evaluate it.
The following is an excerpt from our recent whitepaper, “Why Traditional Cybersecurity Tools Cannot Defend Against Zero-Day and No Signature Attacks,” in which 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 …
In the imperfect, real world, where SOC teams actually live, the SIEM log-based approach is fundamentally flawed. In fact, it tends to add more challenge to the workday for SOC teams, not less.
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.
What does Bitcoin’s energy consumption problem have to do with AI? At a fundamental level, it turns out, some AI applications require similarly massive amounts of computing energy to function.
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.
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.
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.
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.
According to a recent M&A trends survey conducted by Deloitte, 51 percent of 1,000 Executives responsible for Mergers and Acquisitions (M&A) at U.S. companies and private-equity investor firms listed cybersecurity threats as their top concern in executing deals virtually.
MixMode CTO and Chief Scientist, Igor Mezić, has received the prestigious J.D. Crawford Prize from the Society for Industrial and Applied Mathematics (SIAM). The prize is awarded every two years to one individual for a significant accomplishment in the area of nonlinear science. Dr. Mezic received the award for his mathematical theory that makes it easier to understand and speed up an array of previously unsolvable computations in a wide range of applications, including fluid dynamics, energy-efficient design, network security and operations, and complex systems dynamics.
Ultimately, MixMode found, the log-based SIEM approach resulted in five times the amount of data that needed to be stored, a cost that was passed along to the government entity.
The next cybersecurity challenge lies with the advances in quantum computing that are set to revolutionize tech while simultaneously equipping threat actors with a new arsenal of cyberweapons.
Data is the beating heart of every modern organization, but it’s only valuable when it’s accessible, understandable, and most importantly, protected.
What are companies really gaining when they take on SOAR? At a high level, SOAR and legacy platforms are falling far short of their promises. SOCs are left with several pivotal questions.
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.
