Can Your Enterprise Cybersecurity Solution Solve These Two Challenges? You May Be More Vulnerable Than You Realize

Christian Wiens Director of Marketing

Christian Wiens is Director of Marketing at MixMode. He has 10+ years of experience as a cybersecurity professional. He has his BA from The University of California, Berkeley and resides in Austin, TX.

Of all the challenges facing the modern SOC, two stand out among the most persistent and difficult to overcome: an overwhelming volume of false positive alerts and an alarming escalation in zero-day and novel threats that are often imperceptible by legacy systems.

Not only are these two issues extremely challenging to overcome, they are at the root of significant damage to the business side of organizations across the world. Ponemon Institute reports that a full 76% of successful attacks on organization endpoints were zero-day attacks expected to be responsible for damages of around $2.5 trillion in 2022 alone.

As dire as these findings are, all is not lost. Cybercriminals and ill-intenioned nation states are indeed employing sophisticated AI-based techniques to attack their victims, but equally sophisticated cybersecurity solutions can help organizations stay ahead of the game. The reality is that we are well past the point where legacy cybersecurity approaches are effective against common attack methods. Organizations equipped with advanced AI hold the clear advantage.

Legacy Solutions Aren’t Cutting It in 2022

Sadly, the current cybersecurity marketplace is still rife with “legacy” systems — so-called solutions that are ill-equipped to stave off modern zero-day attacks, in particular. Too often, companies continue to partner with vendors offering tech that is simply insufficient, especially when offered as standalone solutions, for example:

Rules-based platforms
Second-wave regression
Bayesian-based
Machine-learning systems

Each of these approaches are inherently limited in their abilities to analyze massive data stores — it would be effectively impossible for these outdated systems to detect novel anomalies at a large enough scale, as the number of rules required would be infinite. Bad actors exploit blindspots created from inevitably biased human input, statistical limitations and historical training data.

False Positive Fatigue

Ultimately, these systems produce so many false positives that require manual review that SOC teams are incapable of keeping up. Every missed review is another potentially missed true positive, and every minute spent by human operators on reviewing innocuous flags is one that could have been spent mitigating true threats detected by more sophisticated security solutions.

Many organizations actually make the problem worse by bringing on more tools that generate more alerts to compensate for inadequacies in their security postures. In fact, a survey by the Cloud Security Alliance revealed that half of enterprises use six or more tools that generate security alerts, resulting in two alarming findings:

40.4% say alerts they receive lack actionable intelligence to investigate
31.9% say they ignore alerts because so many turn out to be false positives

With McAfee reporting that cloud usage has increased the number of transactions occurring at average enterprises each month to more than 2 billion, the implications of adding even more noise to the equation is untenable when it comes to adequate cyber protection.

Because rules-based and second-wave AI-based systems lack the ability to analyze network behaviors in context — to understand usage throughout different time periods or to adapt to acceptable, constantly shifting network behaviors — they are incapable of recognizing and reacting to true, novel threats.

In contrast, MixMode’s AI is self-learning in nature and able to automatically learn an environment with no training data or rules, avoiding bias and blindspots. The AI is highly scalable and is able to analyze 10⁸ wire connections in real time for network packet capture. For a cloud environment, the AI can ingest billions of records per day, including data from Flow Logs, CloudTrail, and so on.

MixMode is Positioned to Meet and Exceed Modern Cybersecurity Threats, Including Zero-Day Attacks

MixMode’s game changing AI is the first commercially available platform leveraging true third-wave AI. Purpose-built for projects at the Defense Advanced Research Projects Agency (DARPA) and the Department of Defense by Chief Scientist Dr. Igor Mezic, MixMode is a standout in the marketplace.

MixMode can accelerate the AI capabilities of large security programs and actually leapfrog the abilities of sophisticated bad actors. And, unlike legacy solutions that leverage first- or second-wave AI based around rules/thresholds or static “training” data, MixMode can be launched and fully unsupervised within a week, versus the typical 6-24 months required by these systems.

Once installed on a network, MixMode gets to work creating a baseline of expected network behavior, identifying anomalies when they arise in real time. This wholly unique approach marks MixMode as the only cybersecurity platform that can predict and surface zero day attacks in real time while ensuring 90%+ alert precision and reduction. Teams can stop wasting time chasing false positives and start focusing on the threats that truly matter.

Learn more about MixMode and set up a demo today.