Splunk for Enterprise Security featuring User Behavior Analytics
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This session will review Splunk’s two premium solutions for information security organizations: Splunk for Enterprise Security (ES) and Splunk User Behavior Analytics (UBA). Splunk ES is Splunk's award-winning security intelligence solution that brings immediate value for continuous monitoring across SOC and incident response environments – allowing you to quickly detect and respond to external and internal attacks, simplifying threat management while decreasing risk. Splunk UBA is a new technology that applies unsupervised machine learning and data science to solving one of the biggest problems in information security today: insider threat. You’ll learn how Splunk UBA works in tandem with ES, or third-party data sources, to bring significant automated analytical power to your SOC and Incident Response teams. We’ll discuss each solution and see them integrated and in action through detailed demos.
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Splunk for Enterprise Security featuring User Behavior Analytics
- 1. Copyright © 2016 Splunk Inc. Enterprise Security & User Behavior Analytics Overview SplunkLive Atlanta,2016 Daniel Christiansen, Sr SE Manager Technical Splunk Guy
- 2. 2 LEGAL NOTICES During the course of this presentation, we may make forward-looking statements regarding future events or the expected performance of the company. We caution you that such statements reflect our current expectations and estimates based on factors currently known to us and that actual events or results could differ materially. For important factors that may cause actual results to differ from those contained in our forward-looking statements, please review our filings with the SEC. The forward- looking statements made in this presentation are being made as of the time and date of its live presentation. If reviewed after its live presentation, this presentation may not contain current or accurate information. We do not assume any obligation to update any forward-looking statements we may make. In addition, any information about our roadmap outlines our general product direction and is subject to change at any time without notice. It is for informational purposes only and shall not be incorporated into any contract or other commitment. Splunk undertakes no obligation either to develop the features or functionality described or to include any such feature or functionality in a future release.
- 3. 3 Agenda Splunk Portfolio Update Enterprise Security Overview and Demo User Behavior Analytics Overview and Demo
- 4. Machine data contains a definitive record of all interactions Splunk is a very effective platform to collect, store, and analyze all of that data Human Machine Machine Machine
- 5. 5 All Data is Security Relevant = Big Data Servers Storage DesktopsEmail Web Transaction Records Network Flows DHCP/ DNS Hypervisor Custom Apps Physical Access Badges Threat Intelligence Mobile CMDB Intrusion Detection Firewall Data Loss Prevention Anti-Malware Vulnerability Scans Traditional Authentication
- 6. 6 App Servers Network Threat Intelligence Firewall Web Proxy Internal Network Security Endpoints Splunk as the Security Nerve Center Identity
- 7. 7 Splunk Solutions > Easy to Adopt VMware Platform for Machine Data Exchange PCISecurity Across Data Sources, Use Cases & Consumption Models IT Svc Int Splunk Premium Solutions Rich Ecosystem of Apps ITSI UBA UBA Mainframe Data Relational Databases MobileForwarders Syslog/TCP IoT Devices Network Wire Data Hadoop & NoSQL
- 8. What is Splunk ES?
- 9. Market Leader in Gartner’s SIEM Magic Quadrant* *Gartner, Inc., SIEM Magic Quadrant 2011-2015. Gartner does not endorse any vendor, product or service depicted in its research publication and not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. 2015 Leader and the only vendor to improve its visionary position 2014 Leader 2013 Leader 2012 Challenger 2011 Niche Player 2015
- 10. More Honors – March 2016 ● Best SIEM Solution ● Best Fraud Prevention Solution
- 11. Platform for Machine Data Splunk Enterprise Security Advancing analytics-driven security Security and Compliance Reporting Monitor and Detect Investigate Threats and Incidents Analyze and Optimize Response
- 12. 12 Open Solutions Framework Supports critical security related management framework features 12 Enterprise Security Framework • Notable Events Framework • Thereat Intelligence Framework • Risk Scoring Framework • Identity & Asset Framework Customer Apps APPs / Content Partner Apps APPs / Content Splunk Apps APPs / Content • Export • Import • Share • Summarization Framework • Alerting & Scheduling • Visualization Framework • Application Framework External Instance
- 13. Splunk App for Enterprise Security Pre-built searches, alerts, reports, dashboards, threat intel feeds and workflow. 13 Dashboards & Reports Incident Investigations and Management Statistical Outliers & Risk Scoring Asset & Identity Aware
- 14. What’s new in Splunk Enterprise Security 4.1 ?
- 15. 15 Behavioral Analytics in SIEM Workflow • All Splunk UBA results available in Enterprise Security • Workflows for SOC Manager, SOC analyst and Hunter/Investigator • Splunk UBA can be purchased/operated separately from Splunk Enterprise Security 15 ES 4.1 and UBA 2.2
- 16. 16 Prioritize and Speed Investigations Centralized incident review combining risk and quick search Use the new risk scores and quick searches to determine the impact of an incident quickly Use risk scores to generate actionable alerts to respond on matters that require immediate attention. ES 4.1
- 17. 17 Expanded Threat Intelligence ES 4.1 Supports Facebook ThreatExchange An additional threat intelligence feed that provides following threat indicators - domain names, IPs and hashes Use with ad hoc searches and investigations Extends Splunk’s Threat Intelligence Framework
- 18. • Continuously Protect the business against: Data Breaches Malware Fraud IP Theft • Comply with audit requirements • Provide enterprise Visibility 18 Why Splunk for Security and Compliance Top Splunk Benefits • 70% to 90% improvement with detection and research of events • 70% to 95% reduction in security incident investigation • 10% to 30% reduction in risks associated with data breaches, fraud and IP theft • 70% to 90% reduction in compliance labor Top Goals
- 19. Incident Response When working an incident which phase generally takes the longest to complete in your organization? 9% 32% 15% 16% 25% 3% 0% 5% 10% 15% 20% 25% 30% 35% Preparation Identification/Scoping Containment/Mitigation Eradication/Remediation Root Cause Analysis Lessons Learned/Recovery Column % Source: © 2016 Enterprise Management Associates, Inc. N=100
- 20. 20 Adaptive Response Initiative 20 App workflow Network Threat Intelligence Firewall Web Proxy Internal Network Security Identity Endpoints Mission: Bring together the best security technologies to help combat advanced attacks Challenge: Gather / analyze, share, act based on end- to-end context, across security domains Approach: Connect intelligence across best-of-breed: • improve security posture • quickly validate threats • systematically disrupt kill chain
- 21. Splunk ES Demo
- 22. What is Splunk UBA?
- 23. 23 FAMILIAR WITH THESE BREACHES? January 2015 February 2015 February 2015 Morgan Stanley 730K PII Records Anthem Insurance 80M Patient Records Office of Personal Management 22M PII Records July 2015 Pentagon Unclassified Email System 4K PII Records
- 24. 24 WHAT IS THE COMPROMISED / MISUSED CREDENTIALS OR DEVICES LACK OF RESOURCES (SECURITY EXPERTISE) LACK OF ALERT PRIORITIZATION & EXCESSIVE FALSE POSITIVES PROBLEM?
- 25. Splunk User Behavioral Analytics Automated Detection of INSIDER THREATS AND CYBER ATTACKS Platform for Machine Data ANOMALY DETECTION THREAT DETECTION UNSUPERVISED MACHINE LEARNING BEHAVIOR MODELINGREAL TIME & BIG DATA ARCHITECTURE
- 26. CUSTOMER THREATS UNCOVERED ACCOUNT TAKEOVER • Privileged account compromise • Data loss LATERAL MOVEMENT • Pass-the-hash kill chain • Privilege escalation INSIDER THREATS • Misuse of credentials • IP theft MALWARE ATTACKS • Hidden malware activity • Advanced Persistent Threats (APTs) BOTNET, C&C • Malware beaconing • Data exfiltration USER & ENTITY BEHAVIOR ANALYTICS • Login credential abuse • Suspicious behavior
- 27. 27 WHAT CUSTOMERS HAVE TO SAY ABOUT SPLUNK UBA Splunk UBA is unique in its data-science driven approach to automatically finding hidden threats rather than the traditional rules-based approaches that doesn’t scale. We are pleased with the efficacy and efficiency of this solution as it makes the life of our SOC analysts’ way better. Mark Grimse, VP IT Security, Rambus A layered defense architecture is necessary to combat modern-day threats such as cyberattacks and insider threats, and it’s crucial to use a data science driven approach in order to find unknown patterns. I found Splunk UBA to be one of the most advanced technologies within the behavioral analytics space. Randolph Barr, CSO, Saba
- 28. Splunk UBA and Splunk ES Integration SIEM, Hadoop Firewall, AD, DLP AWS, VM, Cloud, Mobile End-point, App, DB logs Netflow, PCAP Threat Feeds DATA SOURCES DATA SCIENCE DRIVEN THREAT DETECTION 99.99% EVENT REDUCTION UBA MACHINE LEARNING IN SIEM WORKFLOW ANOMALY-BASED CORRELATION 101111101010010001000001 111011111011101111101010 010001000001111011111011
- 29. What’s New in UBA 2.2
- 30. 30 Enhanced Insider Threat and Cyber Attack Detection DETETION Threat Detection Framework • Custom threat modeling with anomalies Expanded Attack Coverage • Data access and physical data loss New Viewpoint • Precision, prioritization and correlation of alerts with anomalies UBA 2.2
- 31. 31 Create custom threats using 60+ anomalies. Create custom threat scenarios on top of anomalies detected by machine learning. Helps with real-time threat detection and leverage to detect threats on historical data. Analysts can create many combinations and permutations of threat detection scenarios along with automated threat detection. Detection : Custom Threat Modeling Framework UBA 2.2
- 32. 32 Detection : Enhanced Security Analytics Visibility and baseline metrics around user, device, application and protocol 30+ new metrics USER CENTRIC DEVICE CENTRIC APPLICATION CENTRIC PROTOCOL CENTRIC Detailed Visibility, Understand Normal Behavior UBA 2.2
- 33. 33 Context Enrichment Citrix NetScaler (AppFlow) FireEye Email (EX) Symantec DLP Bit9/Carbon Black Digital Guardian And many more…. Improved Precision and Prioritization of Threats Risk Percentile & Dynamic Peer Groups Support for Additional 3rd Party Devices UBA 2.2
- 34. Splunk UBA Demo
- 35. 35 SEPT 26-29, 2016 WALT DISNEY WORLD, ORLANDO SWAN AND DOLPHIN RESORTS • 5000+ IT & Business Professionals • 3 days of technical content • 165+ sessions • 80+ Customer Speakers • 35+ Apps in Splunk Apps Showcase • 75+ Technology Partners • 1:1 networking: Ask The Experts and Security Experts, Birds of a Feather and Chalk Talks • NEW hands-on labs! • Expanded show floor, Dashboards Control Room & Clinic, and MORE! The 7th Annual Splunk Worldwide Users’ Conference PLUS Splunk University • Three days: Sept 24-26, 2016 • Get Splunk Certified for FREE! • Get CPE credits for CISSP, CAP, SSCP • Save thousands on Splunk education!
- 36. Thank You!
Notes de l'éditeur
- Splunk excels at creating a data fabric Machine data: Anything with a timestamp, regardless of incoming format. Throw it all in there! Collect it. Store it in one place. Make it accessible for search/analytics/reporting/alerting. DETECTION NOT PREVENTION! ASSUME BREACH! So we need a place we can go to DETECT attacks. DETECT breaches. DETECT the “weird.” So if you had a place to see “everything” that happened… ….what would that mean for your SOC and IR teams?
- Key part of IT security is protecting confidential data. Which means detecting advanced threats, like cybercriminals or malicious insiders, before they can steal your data. To detect or investigate them, you need non-security and security data because advanced threats avoid detection from signature-based security products; the fingerprints of an advanced threat often are in the “non-security” data. Most traditional SIEMs just focus on gathering signature-based threats which do *not* have the fingerprints of advanced threats. Also the above scenario is worse if there is no SIEM. Instead point UIs and grep are used and aggregating data is very manual and time consuming.
- We see Splunk as your security nerve center. Security organizations are moving towards putting Splunk at the center of everything. . There’s literally nothing in your environment today when it comes to data that Splunk cannot either ingest or leverage. Just a few of those categories are shown here – some of them are quite typical, like your proxy and firewall data. Others less so – your internal badge readers and cameras, for example. Or the ability to correlate all of your data artifacts with IOCs from your threat intelligence sources. All in one place, all at scale, all in real time. That doesn’t mean that Splunk is always the first place that people go – sometimes Splunk may be feeding another tool, like a traditional SIEM. But Splunk always ends up being the place to see “all of the detail” and the place where customers can mash up the data between many disparate sources.
- The Splunk platform consists of multiple products and deployment models to fit your needs. Splunk Enterprise – for on-premise deployment Splunk Cloud – Fully managed service with 100% SLA and all the capabilities of Splunk Enterprise…in the Cloud Splunk Light – log search and analytics for small IT environments Hunk – for analytics on data in Hadoop The products can pull in data from virtually any source to support multiple use cases. Splunk Apps extend and simplify deployments by providing pre-packaged content designed for specific use cases and data types.
- Our rapid ascent reflects the customer traction we have and value we deliver to customers – with thousands of security customers and 40% year-over-year growth, we are the fastest growing SIEM vendor in the market. 2011 was our first time in the MQ; In 2 short years we raced up to the top quadrant in the MQ.
- So our vision was to create flexible, yet powerful. Of course open frameworks where we can nurture and embrace our overall eco-system which includes, customer, resellers, technology partners and even students who wants to develop cools features, rules, intelligent feeds etc. on top of ES. the community can easily share the knowledge or provide a mechanism to accelerate the innovation trends. Customers, vendors and third parties can create and extend the functionality of ES, and run the contents within the ES framework. The content can be imported and exported. Developers can share new apps and modules internally, / or distribute them to the Splunk community on splunkbase Content packs have access to ES specific functionality, / including notable events, the risk framework, and the identity framework.
- All of this rich capability is delivered through Pre-built searches, dashboards, reports and workflows. Your analysts are enable to investigate alerts, maintain a continuous monitoring posture and hunt for unusual activity Manage and investigate incidents by correlating event data and contextual information from any data source Pre-built statistical capabilities identify unusual activity and reduce false positives Automated Threat Intel Integration ensures that new information is rapidly integrated into alerts and investigations Enterprise Security delivers pre-built reports, dashboards, workflows across all security domains. Including wire data, end points, network, access and identity management
- Operational issues and challenges. Use dashboards, alert (correlation), correlate against observables Use them for adhoc searching and swimlanes
- a. Continuation of integration….enabled in depth investigation bring UBA anomaly as sourcetype. Significant because all field in ES is available b. Describe the solution. Value of ES, Notable Events…IR. Add context C. Increasing Threat Intel... Mention leadership and WP. Coverage.
- a. Continuation of integration….enabled in depth investigation bring UBA anomaly as sourcetype. Significant because all field in ES is available b. Describe the solution. Value of ES, Notable Events…IR. Add context C. Increasing Threat Intel... Mention leadership and WP. Coverage.
- The Adaptive Response Initiative represents the commitment and collective efforts of best-of-breed security industry vendors Participant vendors are collaborating to provide a defense strategy for multi-layered heterogeneous security architectures The strategy enables faster, better-informed decision making across multiple security domains This decision making efficiency helps SOC teams protect against advanced (multi-vector, multi-phased) attacks -- Adaptive Response presents users with new context gleaned from the collective intelligence of domain-specific technologies, to verify and/or apply as threat response Splunk is positioned at the center of Adaptive Response and the resulting coordinated response to advanced threats -- Adaptive Response enables timely, effective disruption of the kill chain and subsequent increase in cost of attacks to threat actors Core capabilities include elimination of manual data gathering steps, and ability to apply appropriate actions (or range of actions), specific to each security domain One key benefit is improved ability to respond and adapt – actions can be manual, approval-triggered, or analytics-driven -- Adaptive Response was conceived as a result of the successes of existing Splunk customers who compelled Splunk and partners to form the initiative Launched at RSA 2016, backed initially by Leading Security Domain Vendors: Carbon Black, CyberArk, Fortinet, Palo Alto Networks, Phantom Cyber, Splunk, Tanium, ThreatConnect and Ziften
- A solution that is real-time, and leverages a big data foundation The ability to model behavior on a multi-entity basis. A set of algorithms which can look at the behavior taking an unsupervised machine learning approach And creating flags for anomalies that are detected. In addition, a multi-layered ML models stitches these anomalies into different threat patterns. Let’s break down these components in detail so that you can explain them to customers successfully. So we mentioned that Splunk UBA uses real time data and is built upon big data architecture. That means that it can scale linerly from analyzing and processing 500 million events per day, per instance to billions and billions of events per day. All you have to do is create a cluster and watch it scale. It can do this because it uses the foundation of big data behind the scenes. There have been a significant amount of patents that have been filed for this technology. Secondly, an important foundational concept with Splunk UBA is that it can profile multiple entities within the organization. With Splunk UBA, we profile users and all the accounts associated to that user, devices the user is accessing, and behavior of the device. Networks the user is typically on, behavior of data and apps over the network. What sort of applications is this user using, and what sort of data sets is he or she accessing. From an activity perspective, what is an individual doing with the data sets. From an access perspective, what is he or she accessing and not accessing? And we create similar model for a host. We say: Who is the host talking to? Who are the users logged into this host? Which are the service accounts which have logged into this host? Which network devices has this host communicated with? What is the amount of traffic, viscosity of traffic, volume of traffic that this host is generating, how is it similar or different to other hosts? What sort of applications have I seen on this host or the applications that are consumed by a user that is logged into this host? What sort of data sets exists on this host? What sort of access rights do I see of a user accessing data sets on this host? So what you are looking at is a matrix, a cross correlation matrix which is being built on behavior models. We do this for network, application, and data. Third advantage Splunk UBA offers is the largest library of un-supervised ML algorithms. The old rules and policy driven framework cannot detect any unknown threats in any organization. As technologies have evolved, we’ve seen supervised machine learning models. Where you would actually train the machine learning algorithm with labeled data and deploy it on a customer site. The only problem is it completely depends on the data sets you create algorithms with. And it’s almost impossible that the data set is going to be significant enough to train the algorithms effectively. Those algorithms are likely to generate false positives or not trigger on certain scenarios. From a foundation perspective, Splunk UBA is unique and we actually invested completely on a new thing by leveraging unsupervised machine learning algorithms. Because our philosophy was the data set isn't enough to train the models on. So you let multiple models stream on data sets of an organization and trigger anomalies. The platform has the largest number of algorithms available when compared to any other vendor. And that significantly helps with the depth and efficacy of detection. Because you actually are running multiple unsupervised machine learning algorithms in the same data set, you’re bubbling up different anomalies, and then you are trying to stage those anomalies in different anomalous patterns. And this is where the next foundation piece comes in. Applying these machine learning algorithms against the behavior baselines you have built. And this is significantly focused towards a hunter centric view. The reason is because customers have a hunting team who need to hunt for anomalous entities, behavior, or patterns within an organization, and they need a starting point. This platform visually explains where the first anomaly has kicked in. And it may not transpire into a threat. But it is a significant improvement in the hunter’s ability to spot the first starting point to start the hunting exercise. The next component that we have in the platform is threat detection. Now again, the threat detection is completely driven off machine learning technology. There are no correlation rules being defined. We let the machine learning algorithms automatically figure out how to stitch different anomalous events that have been identified within their own organization. So think about it this way: When you are analyzing billions and billions of events on a daily basis, you are bound to see thousands of anomalies. Because anomalies are actually facts. There is nothing wrong with that fact. It’s pretty much a true positive. It’s a deviation from a baseline. You need a second layer of machine learning algorithms (in our case its again unsupervised machine learning algorithms), which actually have to look at these hundreds of thousands of different anomalous patterns and figure out how it can stitch, we use advanced techniques such as graph walks. And last, but not the least, Security Analytics. The product has over thirty metrics centered around user, device, application, protocol, etc. The goal is to provide visibility and baseline information across numerous elements within your organization. This helps organizations understand operational elements as well as identifying something unusual based on their experience.
- Highlights… Custom threat modelling Data access Easier Leadership, innovation
- Remind what UBA Highlight the pics on right…custom threat Point out the fact that we now have Rules now with ML. Competitors have rules with Stats
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