DeepTempo enhances cybersecurity with MITRE mapping update

DeepTempo has announced new enhancements to its cybersecurity solution, Tempo, which is integrated into the Snowflake Marketplace, aiming to boost threat detection accuracy and reduce response times.

DeepTempo's Tempo now includes improved fine-tuning capabilities and MITRE mapping integration. This development allows the solution to identify and map detected anomalies to the most likely MITRE ATT&CK sequences, providing users with enhanced context and actionable insights.

Evan Powell, Founder and CEO of DeepTempo, said, "Tempo operates upstream from a customer's existing SIEM, meaning that all enriched data and insights flow seamlessly into current workflows. This ensures that security teams can continue leveraging their SIEM while benefiting from the enhanced intelligence provided by DeepTempo."

"Through the Snowflake Native App Framework and the capabilities of Snowflake Cortex AI, we can deliver improved protection to our users in a quicker and more cost-effective way."

One key feature of the recent updates is the solution's ability to adapt models to specific organisational environments, enhancing the precision of threat detection. Users can finance the enhanced protection and threat isolation directly through their Snowflake account, allowing Tempo to run within their own environment.

Prasanna Krishnan, Head of Collaboration and Horizon at Snowflake, highlighted the importance of the innovation: "The rapid progress of DeepTempo in deploying advanced deep learning based solutions for cybersecurity is exactly the sort of innovation we envisioned when we built the Snowflake Native App Framework. By bringing deep learning and other capabilities to the data within their Snowflake accounts, customers can limit costly data movement and dramatically reduce time to value."

Security teams with pre-defined response strategies can more effectively manage cyber threats using Tempo's MITRE ATT&CK flagged alerts. These alerts integrate with existing SIEM platforms, facilitating prompt and precise reactions. This improvement significantly reduces mean time to respond (MTTR) and has been shown to save valuable minutes or hours during active cyber threats.

Tempo leverages network and cloud flow logs to detect whether types of attacks, such as reconnaissance, lateral movement, or data exfiltration, are occurring. It now automatically tags all stored sequences using the nearest MITRE ATT&CK techniques. Additionally, the solution summarises information into embeddings, which are much smaller than the original logs, improving the speed and efficiency of analytics while reducing the costs associated with log storage and analysis.