The world’s first Dynamic Threat Detection Platform
Learn about MixMode’s Dynamic Threat Detection Solutions
MixMode’s use cases for your cyber initiatives
How customers in different industries utilize MixMode
The financial services industry handles vast amounts of highly sensitive financial information, including customer data, transaction records, and intellectual property, making them a prime target for cyber attacks.
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.
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.
Gartner recently released their newest report titled “Emerging Tech: Security – Improve Threat Detection and Response With AI-Based Behavioral Indications” which covers the emergent need for new AI-Based methods of using behavioral patterns to identify threats.
When businesses trust providers to address needs like cybersecurity, they are entrusting vital intellectual property, the private data of employees, consumers, and others, and often, the very infrastructure the business requires to operate.
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).
Hosted by Mark Ehr, Senior Consulting Analyst for 451 Research Advisors and Igor Mezic, Chief Scientist and CTO for MixMode on Tuesday, November 1st at 1pm EST / 10am PST, they will discuss 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.
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.
Experts have warned that the Russia-Ukraine conflict poses an unprecedented cyber risk for U.S. organizations as well as State and local governments and municipalities.
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.
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.
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.
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.
Every network vulnerability opened new opportunities for hackers to infiltrate systems, steal data and wreak havoc. Several notable security incidents have left governments, private organizations, medical systems and large enterprise networks reeling. Many of these entities have discovered that their security plans are simply not up to the task of mitigating modern cybersecurity threats.
In what the New York Times is calling, “One of the most sophisticated and perhaps largest hacks in more than five years,” malicious adversaries acting on behalf of a foreign government, likely Russian, broke into the email systems of multiple U.S. Federal agencies including the Treasury and Commerce Departments.
SIEM has failed to meet the needs of enterprises in the modern threatscape. One huge reason for this is that over time, most organizations will come to the sad realization that they will never achieve a full enterprise deployment of their SIEM. By its very nature, SIEM is always “in process.” It’s not unusual for an organization to have an SIEM in process for a full decade.
MixMode CTO and Chief Scientist, Igor Mezic, recently contributed an article for Techiexpert that examines three modern AI adversarial attacks, the financial toll they are having on some of our most important systems (including healthcare), and how predictive, third-wave AI is the only future-proof cybersecurity solution to protect organizations from these intelligent attacks.
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.