Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id 8EC44200D02 for ; Sat, 9 Sep 2017 00:32:37 +0200 (CEST) Received: by cust-asf.ponee.io (Postfix) id 8D53F1609EC; Fri, 8 Sep 2017 22:32:37 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id 41D541609ED for ; Sat, 9 Sep 2017 00:32:35 +0200 (CEST) Received: (qmail 31910 invoked by uid 500); 8 Sep 2017 22:32:34 -0000 Mailing-List: contact commits-help@metron.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@metron.apache.org Delivered-To: mailing list commits@metron.apache.org Received: (qmail 31791 invoked by uid 99); 8 Sep 2017 22:32:33 -0000 Received: from Unknown (HELO svn01-us-west.apache.org) (209.188.14.144) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 08 Sep 2017 22:32:33 +0000 Received: from svn01-us-west.apache.org (localhost [127.0.0.1]) by svn01-us-west.apache.org (ASF Mail Server at svn01-us-west.apache.org) with ESMTP id 496443A0312 for ; Fri, 8 Sep 2017 22:32:30 +0000 (UTC) Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit Subject: svn commit: r21536 [3/23] - in /dev/metron/0.4.1-RC3: ./ site-book/ site-book/css/ site-book/images/ site-book/images/logos/ site-book/images/profiles/ site-book/img/ site-book/js/ site-book/metron-analytics/ site-book/metron-analytics/metron-maas-serv... Date: Fri, 08 Sep 2017 22:32:27 -0000 To: commits@metron.apache.org From: mattf@apache.org X-Mailer: svnmailer-1.0.9 Message-Id: <20170908223230.496443A0312@svn01-us-west.apache.org> archived-at: Fri, 08 Sep 2017 22:32:37 -0000 Propchange: dev/metron/0.4.1-RC3/site-book/images/document-properties.png ------------------------------------------------------------------------------ svn:mime-type = application/octet-stream Added: dev/metron/0.4.1-RC3/site-book/images/drive-harddisk.png ============================================================================== Binary file - no diff available. Propchange: dev/metron/0.4.1-RC3/site-book/images/drive-harddisk.png ------------------------------------------------------------------------------ svn:mime-type = application/octet-stream Added: dev/metron/0.4.1-RC3/site-book/images/enable-kerberos-configure-kerberos.png ============================================================================== Binary file - no diff available. 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Propchange: dev/metron/0.4.1-RC3/site-book/img/glyphicons-halflings.png ------------------------------------------------------------------------------ svn:mime-type = application/octet-stream Added: dev/metron/0.4.1-RC3/site-book/index.html ============================================================================== --- dev/metron/0.4.1-RC3/site-book/index.html (added) +++ dev/metron/0.4.1-RC3/site-book/index.html Fri Sep 8 22:32:26 2017 @@ -0,0 +1,311 @@ + + + + + + + + + Metron – + + + + + + + + + + + + + + + + + +
+ + + + + +
+
+
+ + + + + + +
+ +
+
+
+
+ + Built by Maven + +
+
+
+ + +
+ +

Build Status

+

Apache Metron

+

+

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.

+

For the latest information, please visit our website at http://metron.apache.org/

+

Metron can be divided into 4 areas:

+ +
    + +
  1. +

    A mechanism to capture, store, and normalize 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.

    2. + +
  2. +

    Real time processing and application of enrichments 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

    3. + +
  3. +

    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.
      • +
    4. + +
  4. +

    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.

    5. +
+

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.

+

+

Obtaining Metron

+

To obtain a release of Metron, please visit http://metron.apache.org/documentation/#releases

+

This repository is a collection of submodules for convenience which is regularly updated to point to the latest versions. Github provides multiple ways to obtain Metron’s code:

+ +
    + +
  1. git clone –recursive https://github.com/apache/metron
    2. + +
  2. Download ZIP
    3. + +
  3. Clone or download each repository individually
    4. +
+

Option 3 is more likely to have the latest code.

+

+

Getting Started

+

To start exploring the capabilities of Apache Metron follow these instructions to launch Metron in a single-node VM on your own hardware.

+

+

Building Metron

+

Build the full project and run tests:

+ +
+
+
$ mvn clean install
+
+

Build without tests:

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+
+
$ mvn clean install -DskipTests
+
+

Build with the HDP profile:

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+
+
$ mvn clean install -PHDP-2.5.0.0
+
+

You can swap “install” for “package” in the commands above if you don’t want to deploy the artifacts to your local .m2 repo.

+

+

Build Metron Reporting

+

To build and run reporting with code coverage:

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+
+
$ mvn clean install
+$ mvn site site:stage-deploy site:deploy
+
+

Code coverage can be skipped by skipping tests:

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+
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$ mvn clean install -DskipTests site site:stage-deploy site:deploy
+
+

The staged site is deployed to /tmp/metron/site/index.html, and can be viewed by opening the file in a browser.

+

+

Navigating the Architecture

+

Metron is at its core a Kappa architecture with Apache Storm as the processing component and Apache Kafka as the unified data bus.

+

Some high level links to the relevant subparts of the architecture, for more information:

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    + +
  • Parsers : Parsing data from kafka into the Metron data model and passing it downstream to Enrichment.
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  • Enrichment : Enriching data post-parsing and providing the ability to tag a message as an alert and assign a risk triage level via a custom rule language.
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  • Indexing : Indexing the data post-enrichment into HDFS, Elasticsearch or Solr.
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+

Some useful utilities that cross all of these parts of the architecture:

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  • Stellar : A custom data transformation language that is used throughout metron from simple field transformation to expressing triage rules.
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  • Model as a Service : A Yarn application which can deploy machine learning and statistical models onto the cluster along with the associated Stellar functions to be able to call out to them in a scalable manner.
    • + +
  • Data management : A set of data management utilities aimed at getting data into HBase in a format which will allow data flowing through metron to be enriched with the results. Contains integrations with threat intelligence feeds exposed via TAXII as well as simple flat file structures.
    • + +
  • Profiler : A feature extraction mechanism that can generate a profile describing the behavior of an entity. An entity might be a server, user, subnet or application. Once a profile has been generated defining what normal behavior looks-like, models can be built that identify anomalous behavior.
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+ + + + Added: dev/metron/0.4.1-RC3/site-book/js/apache-maven-fluido-1.3.0.min.js ============================================================================== --- dev/metron/0.4.1-RC3/site-book/js/apache-maven-fluido-1.3.0.min.js (added) +++ dev/metron/0.4.1-RC3/site-book/js/apache-maven-fluido-1.3.0.min.js Fri Sep 8 22:32:26 2017 @@ -0,0 +1,21 @@ +/*! + * jQuery JavaScript Library v1.8.0 + * http://jquery.com/ + * + * Includes Sizzle.js + * http://sizzlejs.com/ + * + * Copyright 2012 jQuery Foundation and other contributors + * Released under the MIT license + * http://jquery.org/license + * + * Date: Thu Aug 09 2012 16:24:48 GMT-0400 (Eastern Daylight Time) + */ +(function(a2,aB){var x,af,o=a2.document,aI=a2.location,d=a2.navigator,bg=a2.jQuery,I=a2.$,am=Array.prototype.push,a4=Array.prototype.slice,aK=Array.prototype.indexOf,A=Object.prototype.toString,V=Object.prototype.hasOwnProperty,aN=String.prototype.trim,bG=function(e,bZ){return new bG.fn.init(e,bZ,x)},bx=/[\-+]?(?:\d*\.|)\d+(?:[eE][\-+]?\d+|)/.source,aa=/\S/,aV=/\s+/,D=aa.test("\xA0")?(/^[\s\xA0]+|[\s\xA0]+$/g):/^\s+|\s+$/g,bo=/^(?:[^#<]*(<[\w\W]+>)[^>]*$|#([\w\-]*)$)/,a=/^<(\w+)\s*\/?>(?:<\/\1>|)$/,bf=/^[\],:{}\s]*$/,bi=/(?:^|:|,)(?:\s*\[)+/g,bD=/\\(?:["\\\/bfnrt]|u[\da-fA-F]{4})/g,a0=/"[^"\\\r\n]*"|true|false|null|-?(?:\d\d*\.|)\d+(?:[eE][\-+]?\d+|)/g,bP=/^-ms-/,aU=/-([\da-z])/gi,N=function(e,bZ){return(bZ+"").toUpperCase()},aF=function(){if(o.addEventListener){o.removeEventListener("DOMContentLoaded",aF,false);bG.ready()}else{if(o.readyState==="complete"){o.detachEvent("onreadystatechange",aF);bG.ready()}}},Z={};bG.fn=bG.prototype={constructor:bG,init:function(e,b2,b1){var b0,b3,b Z,b4;if(!e){return this}if(e.nodeType){this.context=this[0]=e;this.length=1;return this}if(typeof e==="string"){if(e.charAt(0)==="<"&&e.charAt(e.length-1)===">"&&e.length>=3){b0=[null,e,null]}else{b0=bo.exec(e)}if(b0&&(b0[1]||!b2)){if(b0[1]){b2=b2 instanceof bG?b2[0]:b2;b4=(b2&&b2.nodeType?b2.ownerDocument||b2:o);e=bG.parseHTML(b0[1],b4,true);if(a.test(b0[1])&&bG.isPlainObject(b2)){this.attr.call(e,b2,true)}return bG.merge(this,e)}else{b3=o.getElementById(b0[2]);if(b3&&b3.parentNode){if(b3.id!==b0[2]){return b1.find(e)}this.length=1;this[0]=b3}this.context=o;this.selector=e;return this}}else{if(!b2||b2.jquery){return(b2||b1).find(e)}else{return this.constructor(b2).find(e)}}}else{if(bG.isFunction(e)){return b1.ready(e)}}if(e.selector!==aB){this.selector=e.selector;this.context=e.context}return bG.makeArray(e,this)},selector:"",jquery:"1.8.0",length:0,size:function(){return this.length},toArray:function(){return a4.call(this)},get:function(e){return e==null?this.toArray():(e<0?this[t his.length+e]:this[e])},pushStack:function(bZ,b1,e){var b0=bG.merge(this.constructor(),bZ);b0.prevObject=this;b0.context=this.context;if(b1==="find"){b0.selector=this.selector+(this.selector?" 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============================================================================== --- dev/metron/0.4.1-RC3/site-book/metron-analytics/index.html (added) +++ dev/metron/0.4.1-RC3/site-book/metron-analytics/index.html Fri Sep 8 22:32:26 2017 @@ -0,0 +1,243 @@ + + + + + + + + + Metron – Metron Analytics + + + + + + + + + + + + + + + + + +
+ + + + + +
+
+
+ + + + + + +
+ +
+
+
+
+ + Built by Maven + +
+
+
+ + +
+ +

Metron Analytics

+

+

Metron analytics consists of:

+ +
    + +
  • Model-as-a-Service (MAAS) access to Machine Learning services
    • + +
  • Profiler and Profiler Client
    • + +
  • Statistics
    • +
+
+
+
+ +
+ + + +