Data- Driven Threat Intelligence: Metrics on Indicator Dissemination and Sharing (#ddti)



Similar documents
Data-Driven Threat Intelligence: Metrics on Indicator Dissemination and Sharing (#ddti)

From Threat Intelligence to Defense Cleverness: A Data Science Approach (#tidatasci)

Secure Because Math: Understanding ML- based Security Products (#SecureBecauseMath)

Threat Intelligence Buyer s Guide

All about Threat Central

Ty Miller. Director, Threat Intelligence Pty Ltd

WHITE PAPER: THREAT INTELLIGENCE RANKING

ThreatSTOP Technology Overview

JUNIPER NETWORKS SPOTLIGHT SECURE THREAT INTELLIGENCE PLATFORM

Operational Lessons from the RSA/EMC CIRC: People, Process, & Threat Intel

Intelligence Driven Security

Indicator Expansion Techniques Tracking Cyber Threats via DNS and Netflow Analysis

Cyber Security Metrics Dashboards & Analytics

EVILSEED: A Guided Approach to Finding Malicious Web Pages

Open Source Threat Intelligence. Kyle R Maxwell (@kylemaxwell) Senior Researcher, Verizon RISK Team

Modern Approach to Incident Response: Automated Response Architecture

Defending Networks with Incomplete Information: A Machine Learning Approach. Alexandre

The Third Rail: New Stakeholders Tackle Security Threats and Solutions

Threat Intelligence: An Essential Component of Cyber Incident Response. Jeanie M Larson, CISSP-ISSMP, CISM, CRISC

Cyber Security Summit 2015

Defending against Cyber Attacks

THE EVOLUTION OF SIEM

Threat Intelligence: Friend of the Enterprise

FROM INBOX TO ACTION AND THREAT INTELLIGENCE:

Threat Intelligence for Dummies. Karen Scarfone Scarfone Cybersecurity

Big Data in Action: Behind the Scenes at Symantec with the World s Largest Threat Intelligence Data

After the Attack: RSA's Security Operations Transformed

Unified Security, ATP and more

Analytic and Predictive Modeling of Cyber Threat Entities J. Wesley Regian, Ph.D.

A Primer on Cyber Threat Intelligence

Applying Machine Learning to Network Security Monitoring. Alex Pinto Chief Data Scien2st

Palo Alto Networks. October 6

Threat Intelligence Platforms: The New Essential Enterprise Software

Effective Methods to Detect Current Security Threats

Eight Essential Elements for Effective Threat Intelligence Management May 2015

AMPLIFYING SECURITY INTELLIGENCE

Into the cybersecurity breach

Coordinating Attack Response at Internet Scale (CARIS)

Cymon.io. Open Threat Intelligence. 29 October 2015 Copyright 2015 esentire, Inc. 1

The session is about to commence. Please switch your phone to silent!

Concierge SIEM Reporting Overview

Getting Started Practical Input For Your Roadmap

Analyzing Targeted Attacks through Hiryu An IOC Management and Visualization Tool. Hiroshi Soeda Incident Response Group, JPCERT/Coordination Center

Regional cyber security considerations for network operations. Eric Osterweil Principal Scientist, Verisign

What s New in Security Analytics Be the Hunter.. Not the Hunted

Separating Signal from Noise: Taking Threat Intelligence to the Next Level

Security strategies to stay off the Børsen front page

Network Security Deployment (NSD)

Achieving Actionable Situational Awareness... McAfee ESM. Ad Quist, Sales Engineer NEEUR

DNSwitness: A Generic Platform For DNS-based Measurements

Dealing with Big Data in Cyber Intelligence

Cyber Security. BDS PhantomWorks. Boeing Energy. Copyright 2011 Boeing. All rights reserved.

Threat Intelligence is Dead. Long Live Threat Intelligence!

Security Analytics for Smart Grid

Effective Methods to Detect Current Security Threats

APPLICATION PROGRAMMING INTERFACE

Rethinking Information Security for Advanced Threats. CEB Information Risk Leadership Council

Comprehensive Malware Detection with SecurityCenter Continuous View and Nessus. February 3, 2015 (Revision 4)

Threat Intelligence: The More You Know the Less Damage They Can Do. Charles Kolodgy Research VP, Security Products

The Role of Threat Intelligence and Layered Security for Intrusion Prevention in the Post-Target Breach Era

Cyber Threat Intelligence Move to an intelligencedriven cybersecurity model

STARTER KIT. Infoblox DNS Firewall for FireEye

KEY TRENDS AND DRIVERS OF SECURITY

Take control of your communications, to achieve productivity through intelligence and insight.

The Importance of Cyber Threat Intelligence to a Strong Security Posture

Cyber Threats Insights from history and current operations. Prepared by Cognitio May 5, 2015

Efficacy of Emerging Network Security Technologies

Speaker Info Tal Be ery

How To Create An Insight Analysis For Cyber Security

Solera Networks, A Blue Coat Company SOLERA NETWORKS BIG DATA SECURITY ANALYTICS

State of the Cloud DNS Report

Take the Red Pill: Becoming One with Your Computing Environment using Security Intelligence

GETTING REAL ABOUT SECURITY MANAGEMENT AND "BIG DATA"

Embedded inside the database. No need for Hadoop or customcode. True real-time analytics done per transaction and in aggregate. On-the-fly linking IP

Enabling Security Operations with RSA envision. August, 2009

LASTLINE WHITEPAPER. Using Passive DNS Analysis to Automatically Detect Malicious Domains

Fostering Incident Response and Digital Forensics Research

DNS Firewalls with BIND: ISC RPZ and the IID Approach. Tuesday, 26 June 2012

Transcription:

Data- Driven Threat Intelligence: Metrics on Indicator Dissemination and Sharing (#ddti) Alex Pinto Chief Data Scientist Niddel / MLSec Project @alexcpsec @MLSecProject Alexandre Sieira CTO Niddel @AlexandreSieira @NiddelCorp

MLSec Project / Niddel MLSec Project research- focused branch of Niddel for open- source tools and community building Niddel builds Magnet, the Applied Threat Intelligence Platform focused on detecting breaches and malware activity Looking for trial prospects and research collaboration More info at: niddel.com mlsecproject.org

Agenda Cyber War Threat Intel What is it good for? Combine and TIQ- test Measuring indicators Threat Intelligence Sharing Future research direction (i.e. will work for data) HT to @RCISCwendy

Presentation Metrics!! 50- ish Slides 3 Key Takeaways 2 Heartfelt and genuine defenses of Threat Intelligence Providers 1 Prediction on The Future of Threat Intelligence Sharing

What is TI good for (1) Attribution

What is TI good for anyway? TY to @bfist for his work on http://sony.attributed.to

What is TI good for (2) Cyber Maps!! TY to @hrbrmstr for his work on https://github.com/hrbrmstr/pewpew

What is TI good for anyway? (3) How about actual defense? Strategic and tactical: planning Technical indicators: DFIR and monitoring

Affirming the Consequent Fallacy 1. If A, then B. 2. B. 3. Therefore, A. 1. Evil malware talks to 8.8.8.8. 2. I see traffic to 8.8.8.8. 3. ZOMG, APT!!!

But this is a Data- Driven talk!

Combine and TIQ- Test Combine (https://github.com/mlsecproject/combine) Gathers TI data (ip/host) from Internet and local files Normalizes the data and enriches it (AS / Geo / pdns) Can export to CSV, tiq- test format and CRITs Coming Soon : CybOX / STIX / SILK /ArcSight CEF TIQ- Test (https://github.com/mlsecproject/tiq- test) Runs statistical summaries and tests on TI feeds Generates charts based on the tests and summaries Written in R (because you should learn a stat language)

https://github.com/mlsecproject/tiq- test- Summer2015

Using TIQ- TEST Feeds Selected Dataset was separated into inbound and outbound TY to @kafeine and John Bambenek for access to their feeds

Using TIQ- TEST Data Prep Extract the raw information from indicator feeds Both IP addresses and hostnames were extracted

Using TIQ- TEST Data Prep Convert the hostname data to IP addresses: Active IP addresses for the respective date ( A query) Passive DNS from Farsight Security (DNSDB) For each IP record (including the ones from hostnames): Add asnumber and asname (from MaxMind ASN DB) Add country (from MaxMind GeoLite DB) Add rhost (again from DNSDB) most popular PTR

Using TIQ- TEST Data Prep Done

Novelty Test Measuring added and dropped indicators

Novelty Test - Inbound

Aging Test Is anyone cleaning this mess up eventually?

INBOUND

OUTBOUND

Population Test Let us use the ASN and GeoIP databases that we used to enrich our data as a reference of the true population. But, but, human beings are unpredictable! We will never be able to forecast this!

Is your sampling poll as random as you think?

Can we get a better look? Statistical inference- based comparison models (hypothesis testing) Exact binomial tests (when we have the true pop) Chi- squared proportion tests (similar to independence tests)

Overlap Test More data can be better, but make sure it is not the same data

Overlap Test - Inbound

Overlap Test - Outbound

Uniqueness Test

Uniqueness Test Domain- based indicators are unique to one list between 96.16% and 97.37% IP- based indicators are unique to one list between 82.46% and 95.24% of the time

I hate quoting myself, but

Key Takeaway #1 Key Takeaway #1 MORE!= BETTER Threat Intelligence Indicator Feeds Threat Intelligence Program

Intermission

Key Takeaway #2

Key Takeaway #1 "These are the problems Threat Intelligence Sharing is here to solve! Right?

Herd Immunity, is it? Source: www.vaccines.gov

Herd Immunity would imply that other people in your sharing community being immune to malware A meant your likelihood of infection from it wa negligible regardless of controls you applied.

Threat Intelligence Sharing How many indicators are being shared? How many members do actually share and how many just leech? Can we measure that? What a super- deeee- duper idea!

Threat Intelligence Sharing We would like to thank the kind contribution of data from the fine folks at Facebook Threat Exchange and Threat Connect and also the sharing communities that chose to remain anonymous. You know who you are, and we you too.

Threat Intelligence Sharing Data From a period of 2015-03- 01 to 2015-05- 31: - Number of Indicators Shared Per day Per member Not sharing this data privacy concerns for the members and communities

Update frequency chart

OVERLAP SLIDE

OVERLAP SLIDE

UNIQUENESS SLIDE

MATURITY?

Reddit of Threat Intelligence?

Key Takeaway #1 'How can sharing make me better understand what are attacks that are targeted and what are commodity?'

Key Takeaway #3 Key Takeaway #1 (Also Prediction #1) TELEMETRY > CONTENT

More Takeaways (I lied) Analyze your data. Extract more value from it! If you ABSOLUTELY HAVE TO buy Threat Intelligence or data, evaluate it first. Try the sample data, replicate the experiments: https://github.com/mlsecproject/tiq- test- Summer2015 http://rpubs.com/alexcpsec/tiq- test- Summer2015 Share data with us. I ll make sure it gets proper exercise!

Q&A? Feedback! Thanks! Alex Pinto @alexcpsec @MLSecProject @NiddelCorp Alexandre Sieira @AlexandreSieira @MLSecProject @NiddelCorp The measure of intelligence is the ability to change." - Albert Einstein