Can your cyber tools be leveraged against any stream of data? If not, it’s no exaggeration to say your organization is sitting vulnerable to bad actors.
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.
The trickle-down problem of data overload
SOCs are faced with an endlessly streaming virtual mountain of data that must be stored, aggregated, and managed in order to extract the information needed to detect threats. Organizations simply do not have the time to analyze every morsel of that data — often, even when cybersecurity platforms flag unfamiliar data, alerts are ignored. So many of those alerts wind up being false positives that it’s an unfortunate gamble too many teams have been willing to take.
Over time, SOCs wind up sifting through the same data, again and again, to develop an understanding of their organizations’ security postures. The burden is massive both financially and in terms of human work hours — it’s a problem that births a whole host of other issues:
- An inability to comply with data privacy regulations
- Over-reliance on historical data stores that are woefully out of date versus current realities
- Human error and oversights that require time-consuming fixes
- Ultimately, an increase in attacks arising internally and externally
No matter how many tools organizations add to legacy approaches like SIEM, too much data is still too much data. Rules-based platforms linked to historical data are inherently flawed. By their very nature, they are unable to respond to real-time threats in the real world.
MixMode can monitor any stream of data for threats and anomalies
The MixMode platform, which is driven by third-wave, context-aware AI, takes all data streams into account. The system can ingest data from literally any stream that includes a timestamp and then deliver actionable insights, for example:
- Endpoint data
- SIEM data
- On-prem network data
- Public cloud data
In a way, MixMode is an intelligent filter that can reduce false positive alerts and provide predictive insights, making the overall approach more efficient and cost-effective. It acts as a kind of centralized dispatcher, telling each disparate platform where to focus on which emerging threats should be prioritized.
MixMode allows organizations with established cybersecurity approaches to significantly improve their existing security postures without starting from the ground-up. The platform complements automated response and SOAR platforms by optimizing the prioritization of anomalies, events and alerts, reducing costs and the burden on a typical SOC team by 20 times or more.
MixMode empowers organizational decision makers with unique, high-level insights
As the MixMode platform ingests data across multiple streams, it performs AI-driven analytic calculations on a combination of SIEM, endpoint, public cloud, Bro/Zeek and other sensor data, yielding information characteristic of an attack and shining light on malicious activity from multiple angles. MixMode’s underlying algorithmic approach sits in stark contrast to the majority of network security AI platforms, which typically build customized algorithms for each type of security event.
MixMode AI is highly scalable — the platform can analyze 108 wire connections in real time for network packet capture, and in cloud environments, the AI can ingest literally billions of records each day from sources like Flow Logs and Cloudtrail.
Ultimately, MixMode complements and improves the entire security suite, making it more efficient, more precise and, indeed, more intelligent.
Learn more about MixMode, and set up a demo today.
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