Shannon Lawson, CISO for the City of Phoenix, and Geoffrey Coulehan, Head of Sales for MixMode recently joined forces for a fireside chat at the Evanta CISO Summit in Phoenix, AZ. Lawson and Coulehan have been partnering together for almost three years to transform the City’s cybersecurity initiatives and Security Operations Center (SOC).
In the report, 451 Research explains why security analytics needs to include advanced Third-Wave AI, which autonomously learns normal behavior and adapts to constantly changing network environments, to address the next generation of cyberthreats and increase SOC productivity.
It’s the open secret no one’s talking about — too many cybersecurity solutions in the marketplace stand no chance of providing comprehensive coverage because they are incapable of handling data arising from all sources. Many available solutions are effectively legacy platforms hiding within fresh marketing packages.
Network detection and response, or NDR, has been established as a key tool for companies seeking to improve their threat response. It has become a network security strategy which developed in response to perceived shortcomings in existing network security systems.
MixMode’s Head of Sales and Alliances, Geoff Coulehan, shares how MixMode was able to identify critical risk factors coming from inside bad actors that had gone undetected by a large U.S. city’s SIEM and UBA platforms despite their multi-year deployments and their decision to decommission their User Behavior Analytics (UBA) platform.
Trying to decipher Cybersecurity jargon can feel like trying to make sense out of a spoonful of alphabet soup. Is your SIEM equipped with sufficient NTA? What about your XDR? Or wait, was it NDR? What’s IRM, anyway? And whatever happened to UEBA?
When Cybersecurity teams assume that log-based platforms are the best available network security solutions, they have made a decision to invest in “bad gas.” These products will cost more and deliver less than systems enhanced by context-aware AI.
ou may be surprised to learn that log data is proprietary to each security platform vendor. There is no standard format or even a standard labeling mechanism. Your data only has context within the parameters of your SIEM vendor.
Security information and event management (SIEM) is a security management approach that combines two core functions: SIM (security information management) and SEM (security event management).
As SIEM evolved, vendors began bolting on NDR (network detection and response) and NTA (network traffic analysis) to their base SIEM offerings. The hope (and promise) was that these tools would add the real-time security solution that was lacking with SIEM technology.
A jumble of ineffective, incomplete, extremely expensive platforms that don’t meet the fundamental challenges faced by enterprise SOC teams in the early 2020s is not sustainable.
In partnership with Ravenii, our 60-minute talk was hosted by MixMode’s Head of Sales and Alliances, Geoff Coulehan, CEO of Ravenii, Jeff Shipley, and MixMode’s CTO & Chief Scientist, Igor Mezic. They discussed key topics including:
We recently released a new video to better explain how MixMode’s next-generation cybersecurity anomaly detection platform combines the functionality of SIEM, NDR, NTA and UEBA for advanced threat detection, zero day attack identification, false positive alert reduction, forensic investigation and more.
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.
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.
