ht t17
TRANSCRIPT
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Session ID:
Session Classification:
Patrick Reidy
Chief Information Security Officer
Federal Bureau of Investigation
HT-T17 General Interest
Combating the Insider Threat: Real World Lessons
Kate Randal
Insider Threat Analyst / Lead Researcher
Federal Bureau of Investigation
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► The views expressed in this presentation are those of
the presenter and do not reflect the official policy or
position of the Department of Justice, the Federal
Bureau of Investigation, or the U.S. Government, nor
does it represent an endorsement of any kind.
Disclaimer and Introduction
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1 Insider threats are not hackers
2 Insider threat is not a technical or “cyber security” issue alone
3 A good insider threat program should focus on deterrence, not detection
4 Detection of insider threats has to use behavioral based techniques
5 The science of insider threat detection and deterrence is in its infancy
The 5 Lessons
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Our IA Program & Evolution
Threat focus:
Computer intrusion
Protection: N/W
perimeter, firewalls,
IDS, proxies, A/V,
DHCP, DNS
Detection technique:
signature based
Threat focus: APT
Protection: +
Internal N/W, host
A/V, OS, application
logs, email, net flow
Detection
technique: + N/W
anomaly
Threat focus: Insider
Protection: + DLP,
DRM, Personnel
data, data object
interaction, non-N/W
data
Detection
technique: + data
mining, behavioral
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► NOT hackers
► NOT the most common threat
► People who joined
organizations with no malicious
intent
► Most tools and techniques are
designed with the hacker in
mind
Lesson #1: The Misunderstood Threat
VS. +
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► We lose most battles 2 feet from the computer screen
► 24% of incidents, 35% of our time
► The “knuckle head” problem
► Policy violations, data loss, lost equipment, etc.
► Address with user training campaigns & positive social engineering ► 7% drop incidents since last
year
Not The “Knuckle Head” Problem
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Insider Threat Impact: Industry Reports
► Insider threat is not the most numerous type of threat
► 1900+ reported incidents in the last 10 years
► ~ 19% of incidents involve malicious insider threat actors
► Insider threats are the most costly and damaging
► Average cost $412K per incident
► Average victim loss: ~$15M / year
► Multiple incidents exceed $1 Billion
Sources: Ponemon Data Breach Reports: ‘08, ‘09, ‘10, ’11
IDC 2008
FBI / CSI Reports: ‘06, ‘07, ’08’, ‘09, ‘10/’11
Verizon Business Data Breach Reports: ‘09, ‘10, ‘11, ’12
CSO Magazine / CERT Survey: ‘10, ‘11
Carnegie Mellon CERT 2011 IP Loss Report
Cisco Risk Report ‘08
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► Data from convictions under the Industrial Espionage Act
(IEA) Title18 U.S.C., Section 1831
► Average loss per case: $472M
FBI Case Statistics From IEA 1996 - Present
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► Authorized people using
their trusted access to do
unauthorized things
► Threat actors vs. threats
► Boils down to actors with
some level of legitimate
access, and with some level
of organizational trust
► Misunderstanding example:
The APT is not an insider
threat because they steal
credentials.
Solution: Define the Insider
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Solution: Frame the Threat
Threats
Environmental Human
Internal
Malicious
Espionage I/T
Sabotage Fraud / abuse
IP Theft
Non-malicious
External
Malicious Non-
malicious
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► The Intrusion Kill Chain is excellent for attacks, but
doesn’t exactly work for insider threats
The Intrusion Kill Chain & Insider Threats
Reference: Intelligence-Driven Computer Defense Informed by Analysis of Adversary Campaigns and Intrusion Kill Chain. E.M. Hutchings, M.J. Cloppert, et. al.
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The Insider Threat Cyber “Kill Chain”
Op
eration
al Security
- Recruitment or cohesion - Going from “good” to bad
Recruitment / Tipping point
Search / Recon
Acquisition / Collection
Exfiltration / Action
- Find the data / target - Less time the more knowledgeable the threat
- Grab the data - Data hording
- Game over! - Egress via printing, DVDs / CDs, USBs, network transfer, emails
- Hiding communications with external parties
- Vague searching - Asking coworkers to find data for them
- Use of crypto - Renaming file extensions
- Off hour transfers - Spreading data downloads over multiple sessions
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► Most people don’t evolve into true threats
► Through the continuum there are recurring patters
► Finding these patters is the key
► There are observable “red flags” we call indicators
► Bottom line: insider threats act differently than everyone else
The Insider Threat Continuum
Indicators must be observable and differentiating
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► We trust the threat
► Insider threat programs are not
just policy compliance shops
► 90% of problems are not technical ► Programs do not just bolt into Security
Operations Centers
► Dedicated staff with clear objectives are a
must
Lesson # 2: This is Not a Simple Cyber Security
Problem
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Solution: The Multidisciplinary Approach
Goal:
Detect
Deter
Disrupt Personnel
CI / Intel
Cyber Security
Enemy
People
Data
Identify:
Focus:
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Do You Know Your People? Really?
Serial #: 1234567
A
A
A A
A
A
A
A
Badge# 2345
IP Addrs: 1.1.1.1
Works for Business
Development
703-555-1212
Work schedule
Patterns of activity [email protected]
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The Whole Person Approach
Psychosocial
Contextual
Cyber
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► Who would be targeting your
organization?
► Who would they target inside
your organization?
► Who are the high risk
individuals in your
organization?
Know Your Enemy
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Know Your Data
► What are the crown jewels of your organization?
► What data / people would the enemy want to target?
► Action:
► Identify sensitive data
► Rate top 5 most important systems in terms of sensitive data
► Gather data about the systems
► User data
► Logs
► Document information
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However…
► This is about survival in a hostile
market place
► If your data is secure you can
penetrate risky markets
► Your enemy is your business partner,
are you designed that way?
The Value Proposition of Insider Threat and Data Protection Programs
It’s complex
It’s expensive
It may take years to achieve tangible results
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Lesson #3: Focus on Deterrence Not Detection
► Make environment where
being an insider is not
easy
► Deploy data-centric, not
system-centric security
► Crowd-source security
► Use positive social
engineering
Risk Averse Risk Takers
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► Aren’t security subject matter experts the best to make decisions? ► Nope!
► British scientist who wanted to show empirically that educated people are superior
► Asked “commoners” to guess the weight of an ox at a fair
► Results: ► No single villager correct, but average < 2
lbs. off
► No single SME correct, average SME > 6 lbs off
Solution: Crowdsource Security!
Francis Galton (1822-1911)
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► 13,900 people come to work armed everyday
► Our people are trusted to enforce the law and keep the
country safe
Crowdsourcing Security at the FBI
VS.
If they can train them to use guns, we can train them to use data
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Data Protection Program at the FBI
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Solution: Positive Social Engineering
Users will make good
decisions given timely
guidance
Risk reduction with no
impact to workflow, etc.
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Positive Social Engineering: RESULTS!
Source: Internal FBI Computer Security Logs
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► Nassim Nicholas Taleb wrote in Black Swan:
► The event is a surprise (to the observer)
► The event has a major effect
► After the first recorded instance of the
event, it is rationalized by hindsight, as if
it could have been expected; that is, the
relevant data were available but
unaccounted for in risk mitigation
programs. The same is true for the
personal perception by individuals.
► Lessons:
► True prediction of extremely rare events
(i.e. insider threats) may not be possible
► Don’t waste time and money on the
impossible
► Look for red flag indicators as they
happen
Lesson 4: Detection of Insiders = Kinda Hard
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► A rodent out-predicted our first generation systems
The Issue with Prediction
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Avoid Assumptions
Base your detection mechanisms on empirical evidence!
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► Standard distributions (bell curves) are very rare
► >80% of data movement done by <2% of population
► Hint: Know your data or make huge analytic mistakes
Our Findings in Data Movement
Source: Internal FBI Computer Security Logs
Per User Enterprise Data Egress Over 51st Week of 2012 Data Amount
Users
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The Detection Problem: A Needle in a Stack of Needles
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► Behavioral based detection
► Think more like a marketer and less like
an IDS analyst
► Build a baseline based on users
volume, velocity, frequency, and
amount based on hourly, weekly, and
monthly normal patterns
► Cyber actions that differentiate possible
insiders: data exfiltration volumetric
anomalies
► Socially engineer your threat actors
► Bait works!
Solution: Use Behavioral Detection and Bait
Look at cyber behavioral baselines and lure them out with bait
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Data Mining Techniques
►Rule induction
►Decision trees
►Regression models
►Nearest Neighbor /
Clustering
►Neural networks
Easier
Harder
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► Many want you to believe insider
threats are hackers in order to sell
you things
► IDS, Firewalls, AV, etc. do not work
► No rules are being broken!
► Question vendor claims
► Some great capabilities, but no “out of
the box” solutions
► Data loss prevention, digital rights
management, and IP theft protection
products are maturing
Beware the Silver Bullet
Click Here to Catch Spy
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Lesson #5: Insider Threat Studies and Science
► Operational research about “the insider” is
in its infancy
► Many studies concentrate on only bad
guys
► N is too small
► Findings can be difficult to synthesize into
detection techniques
► Find everyone with Narcissistic
Personality Disorder in your population.
GO!
► Many good resources:
► CERT / DARPA
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Solution: More Focused Research
Known Bad Assumed Good
vs.
► Simple right?
► Why is this research even important?
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Stress
Interpersonal Relationships
Emotional Instability
Change in Habits
Exploitable Work Profile
Work Environment/ Disgruntlement
Vengefulness
Personal Vulnerability
Unauthorized Work Activity
Conflicting Loyalty
Personality/Psychological Issues
Overly Sensitive/ Insecure
Thrill-Seeking
Psychosocial Risk Factors
?
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Our Findings in Psychosocial Indicators
0 20 40 60 80
Engages or threatens to engagein retaliatory behavior against
others
Makes humiliating, insulting, orharassing remarks about others
Does not work well as part of ateam
Shows signs of stress inpersonal life *
Marriage or significantrelationship had a negative
impact
29
27
35
64
52
4
13
9
46
11
FBI Population
Malicious Insiders
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Our Findings in Psychosocial Indicators
Disgruntlement
Responds poorly to criticism
Cannot cope with stress at work
Exhibits a sudden change in work performance
Reacts inappropriately to stress at work
Ego
Acts domineering
Harasses others
Acts argumentative
Superiority issues
Acts selfish
Manipulative
Acts like rules do not apply
Poor teamwork abilities
Irritability
Makes threats
Engages or threatens to engage
in retaliatory behavior
Relationship/Financial Problems
Problems with divorce
Problems with marriage
Stress in home life
Financial problems
Difficulty coping with stress at home
Sudden change in financial status
Irresponsibility
Acts selfish
Emotional Vulnerability
Change in beliefs
Unusual level of pessimism
Unusual level of sadness
Irritability
Makes threats
Difficulty controlling emotions
Get plugged into your HR reporting chain and look for these issues!
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1 Insider threats are not hackers.
Frame and define the threat correctly and focus on the insider threat kill chain
2 Insider threat is not a technical or “cyber security” issue alone
Adopt a multidisciplinary “whole threat” approach
3 A good insider threat program should focus on deterrence, not detection
Create an environment that discourages insiders by crowd sourcing security and interacting with users
4 Detection of insider threats has to use behavioral based techniques
Base detection on user’s cyber baselines and use bait to lure threats out
5 The science of insider threat detection and deterrence is in its infancy
Aid researchers and implement findings at your organizations by plugging into HR
The 5 Lessons & Solutions
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► Carnie Melon University CERT Insider Threat Center
http://www.cert.org/insider_threat/
► Us! [email protected] & [email protected]
Resources for You
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Questions?
Or sit in uncomfortable silence.
Your choice.