Apache Metron-Evolution, Functional Capabilities and Latest News
Metron integrates a variety of open source big data technologies in order to offer a centralized tool for security monitoring and analysis. Metron provides capabilities for log aggregation, full packet capture indexing, storage, advanced behavioral analytics and data enrichment, while applying the most current threat intelligence information to security telemetry within a single platform.
Metron can be divided into 4 areas:
A mechanism to capture, store, and normalise any type of security telemetry at extremely high rates. Because security telemetry is constantly being generated, it requires a method for ingesting the data at high speeds and pushing it to various processing units for advanced computation and analytics.
Real time processing and application of enrichment's such as threat intelligence, geolocation, and DNS information to telemetry being collected. The immediate application of this information to incoming telemetry provides the context and situational awareness, as well as the who and where information critical for investigation
Efficient information storage based on how the information will be used:
Logs and telemetry are stored such that they can be efficiently mined and analyzed for concise security visibility
The ability to extract and reconstruct full packets helps an analyst answer questions such as who the true attacker was, what data was leaked, and where that data was sent
Long-term storage not only increases visibility over time, but also enables advanced analytics such as machine learning techniques to be used to create models on the information. Incoming data can then be scored against these stored models for advanced anomaly detection.
An interface that gives a security investigator a centralized view of data and alerts passed through the system. Metron’s interface presents alert summaries with threat intelligence and enrichment data specific to that alert on one single page. Furthermore, advanced search capabilities and full packet extraction tools are presented to the analyst for investigation without the need to pivot into additional tools.
Big data is a natural fit for powerful security analytics. The Metron framework integrates a number of elements from the Hadoop ecosystem to provide a scalable platform for security analytics, incorporating such functionality as full-packet capture, stream processing, batch processing, real-time search, and telemetry aggregation. With Metron, our goal is to tie big data into security analytics and drive towards an extensible centralized platform to effectively enable rapid detection and rapid response for advanced security threats.
Evolution of Apache Metron
To derstand Apache Metron, we have to first start with the origins of the project which emerged from the Cisco Project called OpenSoc. The below diagram highlights some of the key events in the history of Apache Metron starting with Cisco OpenSoc.
- 2005 to 2008 The Problem - Cyber crime spiked significantly and a severe shortage of security talent arose. The first set of companies alerted to this issue are high profile banks and large organizations with interesting proprietary information to state sponsored agents. All of the best investigators and analysts were gobbled up by multinational banking and financial services firms, large hospitals, telcos, and defense contractors. The Rise of a New Industry, the Managed SOC - Those who could not acquire security talent were still in need of a team. Cisco was sitting on a gold mine of security talent that they had accumulated over the years. Utilizing this talent, they produced a managed service offering around managed security operations centers.
- Post 2008 The Age of Big Data Changed Everything - The Age of Big Data arrived, bringing more streaming data, virtualized infrastructure, data centers emitting machine exhaust from VMs, and Bring Your Own Device programs. The amount of data exploded and so did the cost of the required tools like traditional SIEMs. These tools became cost prohibitive as they changed to data driven licensing structures. Cisco’s ability to operate the managed SOC with these tools was in jeopardy and security appliance vendors took control of the market.
- 2013 OpenSOC is Born and Hadoop Matures - Cisco decided to build a toolset of their own. They didn’t just want to replace these tools but they wanted to improve and modernize them, taking advantage of open source. Cisco released its managed SOC service to the community as Hadoop matured and Storm became available. It was a perfect combination of a use case need and technology. OpenSOC was the first project to take advantage of Storm, Hadoop, and Kafka, as well as migrate the legacy ways into a forward thinking future type paradigm.
- September 2013 thru April 2015The Origins of Apache Metron - For about 24 months, a Cisco team, led by their chief data scientist James Sirota, with the help of a Hortonworks team, led by platform architect Sheetal Dolas, worked to create a next generation managed SOC service built on top of open source big data technologies. The Cisco OpenSOC managed SOC offering went into production for a number of customers in April of 2015. A short time after, Cisco made a couple of acquisitions that brought in third party technologies transforming OpenSOC into a closed source, hardware based version.
- December 2015 Metron Accepted into Apache Incubation - Metron (renamed from OpenSOC) is submitted and accepted as an Apache incubator project. The Metron team builds an extensible, open architecture to account for the variety of tools used in customer environments (thousands of firewalls, thousands of domains and a multitude of Intrusion Detection Systems). Metron’s open approach makes it much easier to tailor to the community’s use cases.
- April 2016 First official Release of Apache Metron 0.1 - After 4 months of hard work and rapid innovation by the Metron community.
Core Functional Capabilities
Apache Metron is a cyber security application framework that provides organizations the ability to ingest, process and store diverse security data feeds at scale in order to detect cyber anomalies and enable organizations to rapidly respond to them.
As the diagram above indicates, the Metron framework provides 4 key capabilities:
- Security Data Lake / Vault - Platform provides cost effective way to store enriched telemetry data for long periods of time. This data lake provides the corpus of data required to do feature engineering that powers discovery analytics and provides a mechanism to search and query for operational analytics.
- Pluggable Framework - Platform provides not only a rich set of parsers for common security data sources (pcap, netflow, bro, snort, fireye, sourcefire) but also provides a pluggable framework to add new custom parsers for new data sources, add new enrichment services to provide more contextual info to the raw streaming data, pluggable extensions for threat intel feeds, and the ability to customize the security dashboards.
- Security Application - Metron provides standard SIEM like capabilities (alerting, threat intel framework, agents to ingest data sources) but also has packet replay utilities, evidence store and hunting services commonly used by SOC analysts.
- Threat Intelligence Platform - Metron will provide next generation defense techniques that consists of using a class of anomaly detection and machine learning algorithms that can be applied in real-time as events are streaming in.
Core Functional Themes
There are four core functional themes that Metron will focus on. As the community around Metron continues to group, new features and enhancements will be prioritized across these four themes.
The 4 core functional themes are the following:
Latest News: Current Release: Apache Metron -0.4.1
Read More: Apache Metron is a scalable, cyber security application framework that provides organizations the ability to detect cyber anomalies and enables rapid response to identified anomalies. Apache Metron software is released under Apache License v2.0. http://metron.apache.org/.
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