Transcript Slide 1

Sigurnost računala i podataka
Mario Čagalj
Sveučilište u Splitu
2013/2014.
Malicious Software
Internet Security & Worms
by Prasad S. Athawale (University at Buffalo)
Computer Security: Principles and Practice
by William Stallings and Lawrie Brown
Code Red Worm Propagation Modeling and Analysis
by Zou et al.
Produced by Mario Čagalj
Malicious Software
 Programs exploiting computing system vulnerabilities
 Known as malicious software or malware
 Malware can be divided into two categories
 Program fragments that need host program - parasitic malware
 E.g. viruses, logic bombs, and backdoors – cannot exist independently of
some actual application program, utility or system program
 Independent self-contained programs
 E.g. worms, bots – can be run directly by the operating system
 We differentiate between software threats that
 Do not replicate – activated by a trigger (e.g., logic bombs, bot)
 Do replicate/propagate itself (e.g., viruses and worms)
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Malicious Software
Malicious
programs
Need host
program
Trapdoors
Logic
bombs
Independent
Trojan
horse
Viruses
Worms
Zombie
(Bot)
Replicate
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Malware Terminology
(1/3)
 Virus: A piece of code that inserts itself into a host program
(infects it). It cannot run independently. It requires that its host
program be run to activate it.
 Worm: A program that can run independently and can propagate
a complete working version of itself onto other hosts on a
network.
 Logic bomb: A program inserted into software by an intruder. It
executes on specific condition (trigger). Triggers for logic bombs
can include change in a file, by a particular series of keystrokes,
or at a specific time or date.
legitimate code
if date is Friday the 13th;
crash_computer();
legitimate code
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Malware Terminology
(2/3)
 Trojan horse: Programs that appear to have one (useful) function
but actually perform another (malicious) function, without the
user’s knowledge.
 Backdoor (trapdoor): Any mechanism that bypasses a normal
security check. It is a code that recognizes for example some
special input sequence of input; programmers can use backdoors
legitimately to debug and test programms.
username = read_username();
password = read_password();
if username is “112_h4ck0r”
return ALLOW_LOGIN;
if username and password are valid
return ALLOW_LOGIN
else return DENY_LOGIN
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Malware Terminology
(3/3)
 Exploit: Malicious code specific to a single vulnerability.
 Keylogger: Captures key strokes on a compromised system.
 Rootkit: A set of hacker tools installed on a computer system
after the attcker has broken into the system and gained
administrator (root-level) access.
 Zombie, bot: Program on infected machine activated to launch
attacks on other machines.
 Spyware: Collects info from a computer and transmits it to
another system.
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Internet Worms
Internet Worms
 Self-replicating program that propagates over Internet
 Using email – a worm mails a copy of itself to other system
 Remote execution capability – a worm executes a copy of itself
on a remote system, either using explicit remote execution
facility or by exploiting flaw (e.g., buffer overflow) in some net
service
 Remote login – a worm logs onto a remote system as a user
then uses commands to copy itself from one to the remote
system
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Internet Worms Uses/Applications
 Launch a DDoS
 Access to Sensitive Information
 Spread Disinformation
 Unknown reasons
 Most generally is the need for being recognized and famous
(never has it been that it was an accident)
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Worm Operation
 Has phases like a virus
 Dormant phase
 Worm is idle, waiting for trigger event (e.g., date, time, program)
 Propagation phase
 Worm searches for other systems, connects to it, copies self to it and
runs (the copy may not be identical – it morphs to avoid detection)
 Triggering phase
 Worm activated by some trigger event to perform intended function
 Execution phase
 The intended function is performed
 E.g., DDoS attack on a specified target
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Worm Operation: Propagation Phase
 To propagate a worm generally performes the following
functions
 Search for other systems to infect by examining different
repositories of remote system addresses
 IP address-space probing to detect vulnerable targets
 Note that this active aquisition/seach phase is not present in viruses
 Establish a connection with a remote system
 Copy itself to the remote system and cause the copy to be run
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Generalized Worm Propagation Model
 In the first stage the infected host searches for vulnerable targets
 When the target is found, the infected host tries to deliver
malcode to the selected target
 Executing the malcode, the target host would be comprimised
 Once the system is compromised, some malware can perform
additional tasks
Infected
Compromise
 Payload refers to those additional
tasks by a worm (DoS, install
backdoors, self-replicate)
Host
System
Select
Target
Payload
Yes
No
Deliver
Malcode
Execute
Payload
Infection
Completed
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Actions in Each of the Stages
 The target selecting stage
 Random IP address probing
 Harvesting email addresses (e.g., from the address book)
 Through file sharing systems
 The malcode delivery stage (can send only a part in this stage)
 A payload associated with buffer overflows
Infected
Compromise
 Using mail of messaging services
Host
System
 Specially crafted HTML pages hosted
on a web server
 Compromising the system
 Execute malcode: email vulnerabilites,
user intervention, automatic execution
 E.g., buffer overflow, backdoors, etc.
Select
Target
Yes
Payload
No
Deliver
Malcode
Execute
Payload
Infection
Completed
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Worm Propagation in Real Life
Morris Worm (Robert Morris in 1988)
 To propagate, worm’s first task was to discover other hosts
known to first infected host that would allow entry from this host
 Exemained system tables that declare which other machines were trusted by this
host, users’ mail forwarding files, remote access control tables, reports from
services that reported the status of net connections
 For each discovered host, various attacks on UNIX systems
 Cracking password file to use login/password to logon to other systems
 Exploiting a bug in the finger protocol
 Exploiting a bug in sendmail
 If any of the three above succeeded have remote shell access
 Sent bootstrap program to the compromised machine’s operating system
 The bootstrap program called back the parent program and downloaded the
reminder of the worm to to copy it over
 About 4000 of the Internet’s approximately 60,000 (at that time)
hosts were infected within 16 hours of the worm’s deployment
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Code Red (July 2001)
 The Code Red worm spreads via a buffer overflow in the
Microsoft Internet Information Server’s (IIS) Indexing Services
 Infection begins by issuing HTTP GET command to a vulnerable IIS system
 The worm probes random IP addresses to spread to other hosts
 During a certain period of time, it only spreads
 It then initiates a denial-of-service attack against a government
Web site by flooding the site with packets from numerous hosts
 Code Red I v2 infected nearly 360,000 servers in 14 hours
 Caused problems to infected servers
 But more importantly, consumed a significant amount of Internet capacity
 Code Red II is a variant that also targets Microsoft IIS
 It also installs a backdoor, allowin a hacker to remotely execute commands
on victim computers
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http://www.caida.org/research/security/code-red/coderedv2_analysis.xml
The Spread of Code-Red v2
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SQL Slammer (January 2003)
 Exploited buffer overflow in Microsoft SQL server
 A single short (400 bytes) packet to UDP port 1434 was sufficient
 The worm infected more than 90 percent of vulnerable hosts
within 10 minutes
 Causing significant disruption to financial, transportation, and government
institutions and precluding any human-based response
 No malicious content, but simply overloaded networks
 The worm’s spreading strategy uses random scanning
 It randomly selects IP addresses, eventually finding and infecting all
susceptible hosts
 Slammer spread nearly two orders of magnitude faster than Code
Red, yet it infected fewer machines
 The fastest computer worm in history (full scanning rate of 55 million
scans per second after only 3 minutes)
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The Spread of SQL Slammer
 Faster than Code Red (CR)
 Slammer is bandwith-limited (its scanner is only only 400 bytes long, a
single UDP packet could exploit the SQL server’s vulnerability)
 CR is latency-limited (its scanner does TCP handshake and therefore has to
wait to receive SYN/ACK packet from target)
 However Slammer’s author made several mistakes in the random number
generator (many active IP addresses simply skipped – fewer infections)
Saturate
d
network
with its
scans
Code Red v2
Slammer
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Modelling Propagation of Worms
Why Modelling?
 Worms spread at an exponential rate
 E.g., 10M hosts in < 5 minutes
 Hard to deal with manual intervention
 How to protect our systems? What are possible effects?
 To be able to defend against future worms, we need to
understand
 Worms propagation patterns
 The impact of human countermeasures (like patching the
computer systems, firewalls, disconnecting devices from the
network, etc.) on worm propagation
 The impact of network traffic (recall the Slammer worm)
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Worm Propagation Modelling
 Simple Epidemic Model
 Uses the time model of Infectious diseases to model Worm propagation
 Three possible states – Susceptible, Infected, Quarantined/Removed
 “Infectious” hosts: continuously infect others
 “Removed” hosts in epidemic area
 Recover and immune to the virus
 Dead because of the disease
 “Removed” hosts in computer area:
 Patched computers that are clean and immune to the worm
 Computers that are shut down or cut off from worm’s circulation
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Simple Epidemic Model
infectious
removed
susceptible
 Assumptions
 The population size (#hosts) is large
 Any host has equal probability to contact any other hosts in system
 Number of contacts is proportional to #infectious X #susceptible
Infectious (I)
contact
Susceptible (S)
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Classical Simple Epidemic Model
 State transition
susceptible
infectious
 N - population of hosts
 S(t) - susceptible hosts; I(t) - infectious hosts at time t
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Classical General Epidemic Model (SIR)
removed
infectious
 State transition susceptible
 N - population of hosts
 S(t) - susceptible hosts
 I(t) - infectious hosts
 R(t) - removed from infectious at rate γ
5
10
x 10
9
8
7
6
=0
=N/16
=N/4
=N/2
5
4
3
2
1
0
10
20
30
40
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Are the Two SIR Models Adequate?
 The classical and general SIR models are not perfectly suitable as
human countermeasures will remove both suceptible and
infectious hosts from circulation
 Human countermeasures include
 Clean and patch: download cleaning program, patches
 Filter: put filters on firewalls, gateways
 Disconnect computers (as in the case of Code Red worm)
 Also, the infection rate  is decreased because of the large
amount of scan-traffic (e.g., the SQL Slammer worm)
 State transition
infectious
susceptible
removed
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Two Factor Worm Model
 Human countermeasures and decreased infection rate 
 N - population of hosts
 S(t) - susceptible hosts
 I(t) - infectious hosts, J(t)=I(t)+R(t) - infected hosts
 R(t) - removed from infectious hosts at rate γ
 Q(t) - removal from susceptible
at rate μ
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Two Factor Worm Model
 Human countermeasures and decreased infection rate 
β(t)S(t) < γ: the number of removed infectious hosts in
a unit time is greater than the number of newly generated
infectious hosts at the same time
Characteristics of Worm Spreading
 Worm growth: slow start, fast spread phase, slow decay
 Speed-ups with more advanced probing techniques
Probing Techniques (Examples)
 Random Scanning
 Local Subnet Scanning
 Routing Worm
 Pre-generated Hit List
 Topological
Probing Techniques: Random Scanning
 32 bit number is randomly generated and used as the IP
address
 Aside: IPv6 worms will be different …
 E.g., Slammer and Code Red I
 Hits black-holed IP space frequently
 Only 28.6% of IP space is allocated
 Aside: can track worms by monitoring unused
addresses
 Honeypots
Probing Techniques: Subnet Scanning
 Generate last 1, 2, or 3 bytes of IP address randomly
 Code Red II and Blaster
 Some scans must be completely random to infect the
whole Internet
Probing Techniques: Routing Worm
 BGP information can tell which IP address blocks are
allocated
 This information is publicly available
 http://www.routeviews.org/
 http://www.ripe.net/ris/
Probing Techniques: Topological
 Uses info on the infected host to find the next target
 Morris Worm used /etc/hosts , .rhosts
 Email address books
 P2P software usually store info about peers that each host
connects to
Probing Techniques: Hit List
 Hit list of vulnerable machines is sent with payload
 Determined before worm launch by scanning
 Gives the worm a boost in the slow start phase
 Skips the phase that follows the exponential model
 Infection rate looks linear in the rapid propagation phase
 Can avoid detection by the early detection systems
Warhol: Hit List + Permutation Scanning
 Infection time estimated to about 15 minutes
 Andy Warhol: “In the future, everybody will have 15 minutes of
fame.”
1. Conventional (Code Red-like )
worm capable of 10 scans/second
2. Fast scanning worm capable of 100
scans/second
3. Warhol worm capable of 100
scans/second using a 10,000 entry
hit-list
No human-driven intervention is
possible when it comes to Warhol
worms (or even more severe flash
worms – infects Internet in tens of
seconds!)
Worm Countermeasures
How to Mitigate the Worm Threat?
S(0) = N
 =/M

M
probe rate of worm
total population (e.g. 232 for IPv4)
“removal” rate

1. Reduce # of susceptible hosts
dS
  I (t ) S (t )
(prevention)
dt
2. Reduce rate of infection
dI
 I (t ) S (t )  I (t )
(suppression)
dt
3. Reduce # of infected hosts
dR
 I (t )
(containment)
dt
Mitigating the Worm Threat
 Prevention
 This aims to reduce the size of the vulnerable population
 Secure programming, applying software updates, AV protection
 Patching
 Generally, patches take days to release – only now that relatively reliable
distribution networks for patches are springing up
 Containment and suppression (the easiest)
 Firewalls, Content Filtering, Automated Routing Blacklists,
disconnecting infected machines
Worm Countermeasures
 Overlaps with anti-virus techniques
 Once worm on system A/V can detect it
 Worms also cause significant net activity
 Scanning for other targets (scan rates 10-10000 scans/second)
 Worm defense approaches include:
 Signature-based worm scan filtering
 Generates a worm scan signature to prevent worm scans from entering a network/host
 Filter-based worm containment
 Focuses on a worm content rather than a scan signature
 Payload-classification-based worm containment
 Packet based checks
 Threshold random walk scan detection
 Exploits randomness in picking destinations to connect to (to detect scanning)
 Rate limiting and rate halting
 Limit or block outgoing traffic when a given threshold exceeded (for fast worms)
Reaction Time Matters
 Worm containment mechanisms should be automated
1. Conventional (Code Red-like )
worm capable of 10 scans/second
2. Fast scanning worm capable of 100
scans/second
3. Warhol worm capable of 100
scans/second using a 10,000 entry
hit-list
4. SQL Slammer 30,000 scans/second
per machine (on 100 Mbps link)
No human-driven intervention is
possible when it comes to Warhol
worms (or even more severe flash
worms – infects Internet in tens of
seconds!)
Closing Words
 Worms pose an ongoing threat of use in attack on a
variety of sites and infrastructures
 The SQL Slammer affected ATMs, 911 services, caused cancelled
flights, etc.
 Worms represent and extremely serious threat to the
safety of the Internet
 Warhol and flash-like worms can infect/affect the
whole Internet in the matter of minutes/seconds
 The need for automated response/containment mechanisms
 Threat awareness important (reduces sussceptible)
 Esspecially for software designers and programmers