TEMPO

# Tempo uses Deep Learning to "see" and isolate incidents that other solutions cannot:

- Cost-effectively and proactively protects the enterprise.
- Useful for one-time audits - and for ongoing monitoring.
- Saves money versus pushing logs into your SIEM, such as Splunk; push the incidents that Tempo identifies instead, and save more than 80% on your SIEM spending.
- Sees novel and known attacks. Achieves very low false positive rates.
- Includes relevant context—including which entities might be impacted and what specific sequences caused concern.
- Combine with other Snowflake data sources, all within the controls of your Snowflake account.
- Maps known anomalies to MITRE tactics to generate context from NetFlow or VPC data.

<br/>Tempo will:

- Identify incidents: seeing concerning patterns of events.
- Enable in-depth analysis of your environment via Forensichat, which has many capabilities, including similarity search, to answer questions such as "how many times have patterns that look like this attack ever occurred?"
- Map incidents to MitreAtt&ck patterns: further assisting your SOC in confirming and triaging the issue.
- Fine-tune itself on a sample of your data: * with a sample of your relevant log type.

As a NativeApp, Tempo inherits your data controls, and DeepTempo, the creators of Tempo, cannot see your data.

Tempo is the first CyberSecurity solution based on a log language model (LogLM). These models are similar to their more familiar cousins, LLMs such as Anthropic's Claude and Llama. Like LLMs, LogLMs are foundation models that apply their understanding across very different environments and in response to differing inputs.<br/><br/>However, Tempo was pre-trained using enormous quantities of logs, as opposed to LLMs, which are trained on GBs of language from the web and elsewhere. Also, Tempo is particularly focused on the pattern of events, including relative and absolute time. Tempo has been shown to be extremely accurate, with a low false positive and false negative rate.<br/><br/>Customers are eligible for free consulting by our security experts that extends beyond the use of Tempo. Please get in touch to learn more.

搜集汇总

背景与挑战

背景概述

TEMPO是基于日志语言模型(LogLM)的网络安全解决方案，通过深度学习分析事件模式来识别已知/新型攻击，具有低误报率和MITRE攻击模式映射能力，可与Snowflake数据源集成并显著降低SIEM成本。