Transcript NewMaliciousLogicx - Department of Math and Computer Science

Malicious Logic
Trojan Horses
Viruses
Worms
Fall 2008
CS 334: Computer Security
Slide #1
Introduction
• Malicious Logic: a set of instructions that
cause violation of security policy
• Idea taken from Troy: to breach an
impenetrable perimeter, have someone from
the inside unknowingly bring you inside
• Example: Name the following script ls and
place in a directory
Set UID of
/tmp.xxsh to UID
of person executing
this script
Remove this
script and run ls
Fall 2008
CS 334: Computer Security
Slide #2
Trojan Horses
• Trojan Horse: A program with an overt
(documented or known) effect and a covert
(undocumented or unexpected) effect
– In example, overt action is to list files, covert is to
create shell that is setuid to user executing script
• There is a key notion here of ``tricked’’
– In the example script, if user root executed this
unintentionally by typing ls in a directory, then we
have a security policy violation.
– If root types out these lines and runs them
intentionally, no violation
– Key problem: system does not know whether user
really intends to run specific set of instructions
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Slide #3
Example: NetBus
• Program that allows attacker to control
Windows NT workstation remotely
– Can download and upload files, intercept
mouse or key strokes, generally be
sysadmin
• Requires small NetBus server on target
machine
– Placed in several small game programs and
other ``fun’’ stuff, then distributed to web
sites where unsuspecting users would likely
download them
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Slide #4
Propogating Trojan Horse
• Propogating Trojan Horse: (also replicating
Trojan Horse) is a Trojan Horse that creates a
copy of itself.
• Ex. Ken Thompson’s compiler
– Added Trojan horse to login program so it accepted a
specific password in addition to user’s password
– Placed code that does this into compiler, so it would
add it whenever it saw a login call. (So not visible in
login code)
– Placed the Trojan horse for compiler into compiler
binary, so if compiler was recompiled it would always
include the trojan horse for login.
– Replaced source for compiler with clean source for
compiler.
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CS 334: Computer Security
Slide #5
Computer Virus
• Computer Virus: A program that inserts itself
into one or more files and then performs some
(possibly null) action
– Insertion Phase: virus inserts itself into file
– Execution Phase: the action is performed
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Slide #6
Virus Pseudocode
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Slide #7
Virus A Trojan Horse?
• Some say YES: Purpose of infected program is
overt action, injections and execution phase is
the covert action
• Some say NO: Virus has no covert purpose.
Its overt purpose is to infect and execute.
• Who cares. Bottom line is that defenses
against Trojan horses inhibit viruses.
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Slide #8
Some History
• 1983: Fred Cohen (at time grad student at
USC) designed virus to acquire privileges on
VAX-11/750 running Unix.
– Obtained all system rights within half hour on
average
– Because virus didn’t degrade response time, most
users never knew system under attack
• 1984: Experiment on UNIVAC 1108 showed
virus could infect that system
– UNIVAC partially implemented Bell-LaPadula Model,
using mandatory protection mechanisms
– Showed that if a system does not prohibit writing
using mandatory access controls, then system does
little, if anything, to prohibit virus propagation
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Slide #9
More History
• 1986-87: Brain (Pakistani) virus infects
IBM PCs
– Alters boot sectors of floppy disks, possibly
corrupting files.
– Spreads to any uninfected floppy inserted
into system.
– Numerous variations have been reported
• 1987: MacMag Peace virus
– Infect Mac, Amiga, among others
– Prints ``universal message of peace’’ on
March 2, 198, then deletes itself.
– Infected copies of Aldus FreeHand program,
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Slide #10
which were subsequently recalled by
Still More History
• 1987: Tom Duff experiments on Unix
with small virus that copies itself into
executable files.
– Not virulent, but when placed in 48
programs on heavily used machine, spread
to 46 different systems and 466 files in 8
days.
– Duff did not violate security mechanism by
seeding files
– Wrote another virus in Bourne shell script.
It could attach itself to any Unix program
– Demonstrated that viruses are not
machine-dependent
and can
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Slide #11
spread to systems of varying architectures
Ok, Even More History
• 1989: Harold Highland develops Lotus 1-2-3
virus
– Virus stored as set of commands for spreadsheet
– Loads automatically when file opened
– Was for demo only, so it changed the value in specific
row and column then spread to other files.
– Demonstrated that macros for office programs on PCs
could contain viruses.
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Virus Types
•
•
•
•
•
•
•
•
Boot Sector Infectors
Executable Infectors
Multipartite Viruses
TSR Viruses
Stealth Viruses
Encrypted Viruses
Polymorphic Viruses
Macro Viruses
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Slide #13
Boot Sector Viruses
• Boot sector is the part of a disk used to
bootstrap the system or mount a disk
– Code in boot sector is executed when system sees
disk for first time
• Boot sector virus is one that inserts itself into
the boot sector of a disk
– When system or disk boots, virus is executed
– Original boot sector code is moved
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Example: Brain Virus
• When system boots from infected disk, virus is
in boot sector and is loaded.
• Moves disk interrupt vector (location 0x13) to
location 0x6d and sets disk interrupt location
to invoke Brain virus.
• Brain virus then loads original boot sector and
continues the boot
• When user reads another floppy, interrupt at
0x13 is invoked, calling Brain virus
– If value 0x1234 in word at location 0x4 of new disk,
boot continues normally. If not, disk is infected
– Infection sometimes overwrite some sectors, thus
the sometimes destructive nature of the Brain virus
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Executable Infectors
• Executable infector: virus that infects
executable programs
– On PC these are COM or EXE viruses
because of the file types they infect
• Viruses prepends or appends itself to
executable
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Example: Jerusalem Virus
• Triggered when infected program is
executed
• Virus puts value 0x0e0 into ax register
and invokes DOS service interrupt
(0x21)
• If on return the high eight bits of ax
contain 0x3, virus is already on system
and original program is invoked
• If not, virus sets itself up to respond to
traps to DOS service interrupt vector
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Slide #17
Example: Jerusalem Virus
• Virus checks date
– if a Friday the 13th and year is not 1987,
virus sets flag in memory to delete files
instead of infecting them
• In memory, virus checks all calls to
DOS service interrupt, looking for files
to be executed (service call 0x4b00)
– Virus checks file name, and deletes file if
destruct bit set (except for COMMAND.COM
file)
– Virus checks last five bytes of file.
Fall 2008
• If string MsDos, file is infected
• If not, virus checks whether name of file ends in E
or M, in which case virus infects it (assuming its a
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Slide #18
COM or EXE
file)Computer Security
Multipartite Viruses
• Virus that can infect either boot sectors or
applications
• Virus typically has two parts, one for each
type. Appropriate part is invoked depending
on circumstances
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Slide #19
TSR Viruses
• Terminate and Stay Resident (TSR)
virus is one that stays active (resident)
in memory after application (or
bootstrapping or disk mounting) has
terminated.
• Can be boot sector or executable
infectors
– Brain and Jerusalem are both TSR viruses
• Non TSR viruses execute only when
host application is executed (or infected
disk mounted, etc)
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Stealth Viruses
• Stealth viruses are those that conceal the
infection of files
• Intercept calls to the OS that access files
– If call is for file attributes, original (uninfected) file
attributes returned
– If call is to read file, uninfected version is returned
– If call is to execute file, infected file is executed
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Example: The Stealth Virus
• Also called IDF virus or 4096 virus
• Modifies DOS service interrupt handler
– Not interrupt vector. This way inspection of
interrupt vectors does not reveal presence
of virus
• If call is for length of file, length of
uninfected file returned
• If request to open file, file is
temporarily disinfected, then reinfected
when file is closed
• Changes last modification time for file
to indicate the file is not infected
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Encrypted Viruses
• Virus that enciphers all of the virus code
except for a small decryption routine
• Anti-virus software looks for known sequences
of code
• To fight this, some viruses encipher most of
code, leaving only small decryption routine
and random cryptographic key in clear
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Example: 1260 Virus
• Uses two keys stored in k1 and k2
• Virus code begins at location sov and ends at
location eov
• Dual keys and shifting of first key prevent
simple xor from uncovering deciphered virus
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Polymorphic Viruses
• A virus that changes its form each time it
inserts itself into another program
• Considered an encrypted virus
• With straight encrypted virus, decryption
portion can be detected!
• Polymorphic viruses designed to defeat this.
– They change instructions in virus to something
equivalent but different. Technique is used to hide
decryption code.
All do same thing!
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Example
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Polymorphic Viruses
• Production of polymorphic viruses has
been automated
– Mutation Engine (ME)
– Trident Polymorphic Engine (TPE)
• Polymorphism can occur at different
levels
– A deciphering algorithm may have two
different implementations
– Two different algorithms may produce same
result (much harder to detect)
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Macro Viruses
• A virus that it composed of a sequence
of instructions that is interpreted rather
than executed directly
• Conceptually no different from ordinary
computer viruses
• Can execute on any system that can
interpret the instructions
• Can infect executables or data files
(data virus)
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Macro Virus
• If infecting executable, must arrange to
be interpreted at some point
– Ex. Duff’s experiments wrapped executables
with shell scripts. Resulting executables
invoked Bourne shell which interpreted
virus code before invoking usual executable
• Macro viruses not bound by machine
architecture – use specific programs
– Any system that runs this program can be
affected, though effects may differ
– Ex. MS Word virus will work on PC, Mac,
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Example: Melissa Virus
• Infected Word 97 and 98 documents on
Windows and Mac systems (written in
Visual Basic)
• Installs itself as the ``open’’ macro and
copies itself into the Normal template
so that any files that are opened are
infected
• Then invokes mail program and sends
copies to names in address book
– On PC spread was through mail
– On Mac, most user didn’t use mail program
spread was notSlide
via
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CSinvokes,
334: Computerso
Security
#30
email.
Computer Worms
• A computer worm is a program that
copies itself from one computer to
another (as opposed to hitching a ride)
• Research on worms began in mid-1970s
– Schopp and Hupp developed distributed
programs to do various tasks. These
probed workstations, to find idle machines
on which they installed code segments do
do work. When other work on machine
started, segments shut down.
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The Internet Worm
• Nov. 2, 1988: program targeted Berkeley and
Sun Unix based machines.
• Within hours of introduction to Internet it had
rendered thousands of computers unusable
• Worm inserted instructions into a running
process on target machine and arranged for
instructions to be executed
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The Internet Worm
• Recovery required disconnection from network
and reboot
– Several critical programs had to be changed and
recompiled to prevent re-infection
– Worse, program disassembly required to determine
whether other malicious effects present
– Fortunately only purpose of worm was self
propagation (could have been much worse!)
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Slide #33
Internet Worm
• Worm took advantage of flaws in some
standard software installed on Unix
systems
• fingerd is a utility that allows users to
obtain information about other users
• gets is a routine that takes input into a
buffer without performing a bounds
check
• sendmail is a program that routes mail
in heterogeneous networks
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fingerd
• Program runs as a daemon (background
process)
– Allows connections from remote programs
– Reads single line of input, sends back
appropriate output
• Code used call to gets routine to get
input. Worm smashed the stack using
this call
• Unfortunately, several routines remain
with such buffer overflow vulnerabilities
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Slide #35
sendmail
• Operates in several modes: worm exploited
debug mode operation
• Sendmail listens on TCP port 25 for attempts
to deliver mail using simple mail transfer
protocol (SMTP)
– When contacted, sendmail enters into dialog to
determine sender, etc.
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sendmail
• Worm used DEBUG command to specify the
recipient of the message as a set of
commands instead of a user address
– This is not allowed in normal mode
– In debug mode, allows testers to verify mail is
arriving without having to invoke address resolution
routines
– That is, testers can run programs to show state of
mail system without separate login connection or
having to send mail
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Aside: Unix Passwords
• Passwords encrypted with premuted
version of DES and ciphertext stored in
world-readable accounting file
• Worm used dictionary attack to break
passwords (sometimes as many as 50%
of the passwords on a system)
• Unix now stores passwords in shadow
password file that can only be accessed
by sysadmin
– And encryption is done using a privileged
routine that delays return for a second or so
(prevents online testing)
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Slide #38
Aside: Trusted Logins
• BSD Unix has nice support for login from
remote machines
• One can specify a list of host/login name pairs
that are assumed to be trusted. Login with
these pairs does not require a password
– hosts.equiv and .rhosts files
• Worm exploited this by trying to locate
machines that might trust the current machine
– How do you think it did this?
– When one found, worm placed itself on the target
machine
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Internet Worm (High level
description)
• Main program: collect info on other machines
on network to which current machine could
connect
– Read config files
– Run system utilities to get info about current state of
network connections
– Used previously mentioned flaws to attempt to
establish bootstrap on these machines.
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Internet Worm (High Level
Description)
• Bootstrap program:
– 99 lines of C code that would be compiled and run on
remote machine
– Once transferred to target machine, it was compiled
and invoked with three command line arguments
• Network address of infecting machine
• Number of network port to connect to on machine to
get copies of the main worm files
• Magic number that acted as one-time challenge
password
– If worm on remote host and port didn’t receive magic
number back, it would immediately disconnect from
bootstrap program
» Possibly to prevent someone from capturing a copy
of the worm by spoofing a Worm server
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Internet Worm (High Level
Description)
• Bootstrap program:
– Connect back with worm that originated it and
transfer a set of precompiled code (binaries) to local
machine
– These binaries represented versions of the main
program for various OS versions and machine
architectures.
– Once binaries transferred, loaded and linked with
standard library routines on host machine, then one
by one run.
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Slide #42
Father Christmas Worm
• Electronic Christmas Card passed around IBMbase networks
– Card was letter instructing recipient to save letter
and run as a program.
– Program drew Christmas Tree (with blinking lights!)
and printed Merry Christmas
• Program checked recipients list of previously
received mail as well as address book, then
sent itself to all these addresses
• Overwhelmed network and forced shutdown
• Macro worm written in high-level job control
language
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Rabbits and Bacteria
• Program that absorbs all of some class
of resource
– Program copies multiply so fast that
resources exhausted. A class of denial of
service attack.
• Ex. (Dennis Ritchie) This will exhaust
disk space or inode tables on a Unix
Version 7 system
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Examples
• Internet worm:
– During infection, opened a port on target machine.
– When another worm tried to infect machine, it
checked port. If opened it assumed machine
infected.
– But apparently to thwart sysadmins opening a small
program on that port, every sixth attack it ignored
the check.
– Lead to many copies of the worm on single machine.
These consumed the CPU.
• Father Christmas:
– Created so much network traffic that network
became unusable and had to be shut down
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Question: Is there an algorithm that
can determine if an arbitrary
program contains replicating code?
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Answer (Cohen): No such algorithm
can exist. It is provably undecidable
whether an arbitrary program
contains a computer virus.
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Logic Bomb
• Logic bomb is a program that executes
malicious logic when some external event
occurs
– E.g. program attacks on specific date
• Disaffected employees who plant Trojan
horses in systems often use logic bombs
– E.g. delete entire payroll roster when employee’s
name is deleted
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Example
• Early 1980s: program posted to
USENET promised to make
administering systems easier
• Directions:
– Unpack shar archive containing program
– Compile program and install as root
• Midway down the shar archive:
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A More Modern Perspective on
Malicious Logic
We’ve talked a bit about classification
and seen an important theoretical
result. Now we consider more recent
developments.
As always thanks to my Berkeley
Colleagues for providing much of the
slides on this modern perspective.
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Outline
• What is a Worm/Virus?
• Why are they created?
• Infection Vectors and Payloads
– How they propagate and what they do
• Worm propagation rates
• Virus/Worm detection/prevention
– File scanners, host scanners, network scanners
– Host monitors
• Targeted Worms and Viruses
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Internet Worms and Viruses
• Self-replicating code and data
– Worms are self-propagating (search network)
• Typically exploit vulnerabilities in an application
running on a machine or the machine’s OS
– Viruses typically require a human interaction before
propagating
• Running e-mail attachment, or click link in e-mail
• Inserting/connecting “infected” media to a PC
• Behavioral invariant: they seek to propagate
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Why Create Worms/Viruses?
• Formerly was a prestige motivation
– Finding bugs, mass infections, …
– 50% of viruses contain crackers’/groups’ names
• Cracking for profit, including organized crime
– Create massive botnets 10-100,000+ machines
infected
• Overloading/attacking websites, pay-per-click scams,
spaming/phishing e-mail, or phishing websites…
– More on botnets later…
– Corporate/personal espionage (SSN, passwords,
docs, …)
• Closing security loopholes
– Is this ethical?
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Revisiting Zotob Virus (August
2005)
• Financially-driven motive
– Infected machines and set IE security to low
(enables pop-up website ads)
– Revenue from ads that now appear
– User may remove virus, but IE settings will likely
remain set to low
– Continued revenue from ads…
• Targeted (among others) ABC, CNN, the
Associated Press, NY Times, Caterpillar Inc,
– Cost an average of $97,000 and 80 hours of cleanup
per company affected.
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Revisiting Zotob Virus (August
2005)
• August 26th, 2005 (two weeks after Zotob)
– Farid Essebar was arrested in Morocco, Atilla Ekici
arrested in Turkey
• September 16, 2006
– Essebar and friend Achraf Bahloul sentenced in
Moroccan court.
• Ekici believed to have bought the worm for
financial gain.
• Believed that Essebar is part of larger group,
the Dark-side Hackers, behind spread of Zotob
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Infection Vectors and Payloads
• Two components to worms and viruses
• Infection vectors
– How they get onto your machine and then propagate
• Payloads
– What they do on your machine
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Infection Vectors
• Network scanning for potential victims (worms)
• Local/server/P2P files (viruses/worms)
• E-mail message components (viruses)
• Web sites (worms/viruses)
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Network Scanning for Potential
Victims (Worms)
• How to scan the network?
– Pick address, try to exploit protocol vulnerabilities
• How to generate addresses?
– Use a PRG, but how to initialize the PRG?
• Same seed on each host (common flaw!)
– Need to generate local seed…
• Generate 32-bit IP address or 4 8-bit parts?
– Is even or uneven probing better?
– Local hosts are likely to be same OS/patch level and
have higher bandwidth
– Also local addr space is denser
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Worm Exploits
• Buffer overflow on servers/clients
– Identify de-serializing errors, send exploit code
– MSBlaster DCOM/RPC exploit
• Forcing protocol parsing errors
– Identify errors in protocol handling/state machine
– Morris worm fingerd remote code exec
• Weak passwords (more on this in a moment)
– Brute force: try name backwards, appended, …
• Out-of-the box configuration errors
– Default ID/password
– Debugging mode enabled (Morris worm sendmail
exploit)
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Infecting via Files
• Factory installed
• Removable media (viruses)
– Floppies, CD/DVD-ROMs, USB drives/keys
• Files on shared servers and P2P networks
(worms/viruses)
– Have to convince user to click to open…
– Or, an infected existing document
• E-mail file attachments (viruses)
– Have to convince user to click to open…
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Infecting via E-mail
• E-mail attachments (viruses)
– Files (see last slide)
– Scripts: Windows Scripting Host
– HTML files: browser exploits (next slide)
• HTML-formatted e-mail messages
– Browser exploits (next slide)
– User clicks on links (leads to browser exploits)
– Windows Scripting Host
• Executes simply by viewing e-mail msg (LoveLetter)
– Embedded images (JPEG/PNG render exploits)
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Why E-mail based Infections?
• E-mail has become globally ubiquitous
– By 2006, e-mail traffic is expected to surge to 60
billion messages daily
• Message Labs scanned 14.7 billion emails
scanned, found >6% were viral
• Nearly all of the most virulent worms of 2004
spread by email (Symantec/Sophos)
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Web Sites (Worms/Viruses)
• Set up malicious server, or infect existing
server
– Porn, Warez/Crackz/Gamez, anti-spyware(!) sites
• Exploit bugs in browser rendering engine
– “Drive-by-download” infection
• ActiveX exploits
– Leverage bugs in ActiveX components
– Enable remote script/code execution
• HTML parsing vulnerabilities
– Redirect to malicious sites
– Cause buffer overflow, or file download and execute
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Types of Payloads
• Bootstrap loader
• Message
• Propagation engine
– System settings/DNS changer, file installer
•
•
•
•
Destructive actions
Zombie software installer
Trojans/Browser Help Objects installer
But, sometimes payloads don’t work
– Inadvertent system crashes instead
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Payloads
• Bootstrap loader
– Used when exploit can only send a small amount of
code/script
– Establishes TFTP connection back to infecting
machine to retrieve real payload
• Message (could be null)
• Propagation engine
– Permanently installs virus/worm by changing system
settings, or replacing/infecting system files (rootkit)
– Infect local/server/P2P documents, music, etc.
• Malicious: disk corruption, or BIOS re-flash
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Payloads
• Zombie software install
– Password cracker
– Spambot or Distributed Denial of Service bot
• Trojans/Browser Help Objects installer
– Adware/spyware install
• Typically, implemented as BHOs
– Collect personal info, logins/passwords for financial
sites, files/data and send to attacker
– Create popups and search redirects
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Fast Propagating Worm/Virus Side
Effects
• Traffic floods network links
– Slammer prevented admins from accessing servers
to shut them down/patch them
– Affected the access links
• Border Gateway Protocol heartbeats monitor links
• Timeouts caused links to drop, stopped worm traffic
• Heartbeats get through, links come back up, worm
traffic flows again (repeat!)
• Overwhelms servers (e-mail/other)
– Denial of service (sometimes intentional)
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Virus/Worm Toolkits
• Dozens of websites and downloadable toolkits
for building worms/viruses
• Make it easy for script kiddies to create new
threats
• But, most are built from common building
blocks with the same polymorphic engines
– Can create signatures for blocks and engines
• Encryption is a looming threat…
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Our Path
• What is a Worm/Virus?
• Why are they created?
• Infection Vectors and Payloads
– How they propagate and what they do
• Worm propagation rates
• Virus/Worm detection/prevention
– File scanners, host scanners, network scanners
– Host monitors
• Targeted Worms and Viruses
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Propagation Rates
• Classic theory
– Function of # vulnerable hosts (N), initial
compromise rate (K), start time (T)
• Logistics equation:
K (tT )
e
a
K(tT )
1 e
– a is the number of infected hosts

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Code Red I Propagation
• Can’t
easily
count
infected
hosts
– Count
scans
instead
• Theory
matches
observed
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Propagation Rates (New Theory)
• Slammer
• Doesn’t
apply to fast
propagating
worms
– Links have
bandwidth /
latency
constraints
– No universal
connectivity
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Other Factors
• TCP (3-way) versus UDP
– Latency between attacker and victim has major
impact for TCP
– Timeout delay when scanning
• Also, function of scan algorithm
– PRN quality
• Broken algorithms mean missed hosts
– Seed computation
– Scan distribution (even or local bias?)
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Propagation Behavior
• More efficient scanning finds victims faster (< 1hr)
• Even faster propagation is possible if you cheat
– Wasted effort scanning non-existent or non-vulnerable
hosts
– Warhol: seed worm with a “hit list” of vulnerable hosts
(15 mins)
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Virus Propagation Rates
• How to determine virus propagation rates?
– Don’t have universal connectivity
• Small worlds effect: 6-degrees of separation
– Have to account for queuing delays
– Limited (delayed) by human interaction rate
– Very hard to model analytically
• E-mail viruses tend to appear first in Asia,
then Europe, finally North/South America
– Follows business day/timezones
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Our Path
• What is a Worm/Virus?
• Why are they created?
• Infection Vectors and Payloads
– How they propagate and what they do
• Worm propagation rates
• Virus/Worm detection/prevention
– File scanners, host scanners, network scanners
– Host monitors
• Targeted Worms and Viruses
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Detection/Prevention Techniques
• File and host scanners and monitors
– Signature-based scanners
• Have “zero” false negatives/positives
• Significant human delay (hours to days)
– Heuristic-based scanners
• Non-zero false negative/positive rates
• Network scanners
• Firewalls
• Throttling
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Signature Generation Requires
Human Intervention
• Human element slows reaction times
–
–
–
–
Malcode collection can take hours
Signature generation can take hours to days
Signature distribution can take hours to days
Novel malcode propagates faster than signatures
• Signature methods are mired in an arms race
– MyDoom.m and Netsky.b slipped through many mail
scanners
– Malcode: polymorphic today, encrypted in future
– Signature-based approach alone is insufficient
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File/Host Scanners and Monitors
• File
– One-time/periodic “scan” or continuous real-time
monitor
– Scan all files on read/write
– Heuristic: look for code similarities (e.g., propagation
engines), not identical matches
• Host scanner
– One-time/periodic “scan” or continuous real-time
monitor
– Scan active processes, bios, registry, … for infections
– Heuristic: examine process memory, look for
anomalous registry entries, …
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Network Scanners
• Place at network ingress point
• Scan all incoming traffic, especially e-mail
– Uses signatures like file scanners
– Also heuristic e-mail scanning (phishing, spam)
• Can also apply exfiltration scanning
– Phishing attempts, viruses/worms that attempt to
transmit personal/sensitive/corporate data
• Scaling and reliability issues
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Firewalls
• Usually deployed at network ingress points
– Default deny all
– Stops worm scans
• Except for public services, like web servers!
• And, trusted servers/clients
– Can lead to complacency
• Remember, network is only one propagation method
• Laptops are a problem
• Partial solution: host-based firewalls
– Now mandatory at many places
– Still need signatures for detection
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Network Throttling
• Heuristic approach: limit #connections/min
– Idea: slow down worm scans or outgoing virus emails
– Algorithm placed in routers
• Limit outbound connections to slow down
worms
• Can’t set a fixed limit, why?
– Users have different sending rates, servers, …
• Inverse throttling
– Tarpits
– Delay connections to non-existent/protected hosts
– Consumes precious OS resources on worm machine
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Our Path
• What is a Worm/Virus?
• Why are they created?
• Infection Vectors and Payloads
– How they propagate and what they do
• Worm propagation rates
• Virus/Worm detection/prevention
– File scanners, host scanners, network
scanners
– Host monitors
• Targeted Worms and Viruses
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Example Scenario
• You arrive at work and start reading e-mail
• In your inbox is a business proposal from your
biggest competitor
• You’re curious so you open and read the
proposal
• You decide to ignore it and continue on with
your work
• Two weeks later you lose your biggest clients
to the competitor, they lowball you on a bid,
announce a better version of your planned
killer product, …
• Fact or fiction?
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Fact!
• You’re the victim of a targeted attack
• Opening the proposal secretly installed a
Trojan horse program
– The Trojan searched your hard drives and network
shares for confidential documents and e-mail
messages
– Then, it sent them out to a server run by your
competitor
• Custom attacks are hard to detect
– One-of nature means no signatures
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Targeted Attacks
• Israel (May 19, 2005)
– 7 businessmen and 11 private detectives arrested for
using Trojan horse for cyber industrial espionage
• Satellite TV, cell phone, auto import business
• Trojan designed by husband-wife pair in
Britain
– Named Rona (variant of Hotword Trojan)
• Caught because husband installed it on fatherin-law’s computer and it posted copies of a
private manuscript online
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Designing a Targeted Attack
• How to profile target to identify OS, SW?
– Send an e-mail message and examine reply!
• User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.0;
en-US; rv:1.5) Gecko/20031007
– More work to determine OS/SW patch levels
• Then craft an attack:
–
–
–
–
–
HTML script vulnerabilities
Embedded/remote images
Web site exploits
Office documents (macros, scripts, …)
Other document types (PDF, PS, …)
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Worm/Virus Summary
•
•
•
•
•
Arms race between creators and protectors
Existing signature approaches are limited
Financial motive poses growing threat
High risk from Warhol worms
Viruses are still a critical threat
– FBI survey of 269 companies in 2004 found that
viruses caused ~$55 million in damages
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An aside: User Authentication
E.g., How can a system tell you’re you?
Unlike “real world” authentication (e.g.,
you recognize someone’s voice over the
phone) computer can’t “recognize”
someone (well, not in the same way).
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The Basics
• Three quantities used to confirm user’s identity
– Something the user knows
• Passwords, PIN numbers, secret handshake, mother’s
maiden name
– Something the user has
• Identity badge, physical key, driver’s license, uniform
– Something the user is
• Biometrics: based on physical characteristics of user (e.g.,
fingerprint, pattern of person’s voice, picture of face).
• These three can be combined
• Password is the most common means of user
authentication to OS
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Passwords
• Although secure in theory, human practice
often degrades quality of this means of
authentication
• Must handle:
– Loss: depending on implementation, it is possible
that no one will be able to restore a lost password.
– Use: Supplying password for each file access can be
inconvenient and time consuming.
– Disclosure: If password disclosed to unauthorized
individual, file becomes immediately accessible. If
password is then changed, all other legitimate users
must be notified.
– Revocation: To revoke one user’s access rights to a
file, someone must change the password, causing
same problems as disclosure.
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Aside: Multifactor Authentication
• This is fancy name for use of additional
authentication information
• E.g., log in allowed only if password check is
valid and
– Log in request received from specific IP address
and/or port AND
– Log in request received during specific time period
(say between 8 a.m. and 5 p.m.
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Aside: Multifactor Authentication
• Two forms if authentication (two-factor
authentication) better than one if both are
strong
– But as number of forms increase, so does
inconvenience
– AND each authentication factor requires system to
manage more security info (which, in addition to
increased protection resources) may also increase
complexity of implementation
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Attacks on Passwords
• Passwords limited as protection devices
because of the relatively small number of bits
of info they contain
• Ways to obtain user’s password (in decreasing
order of difficulty)
–
–
–
–
–
Try them all
Try frequently used passwords
Try passwords likely for the particular user
Search for system list of passwords
Ask the user
• Systems don’t help here, as they often provide
attacker with partial information.
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Loose-Lipped Systems
• Note password authentication is based on
premise that user knows nothing of the
system. But systems often help an attacker
• Consider system messages look like above
(uppercase is system message, lowercase is
user)
– System is identified, and attacker knows adams is
not a valid user name. Intruder can use this with
common surnames to build a list of authorized users.
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Loose-Lipped Systems
• Better: User is not told whether it is the
username or the password that is bad
• But message still provides name of the
system.
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Loose-Lipped Systems
• Best: adversary receives no information until after
successful authentication.
– After all, legitimate user should know the name of the
system, so why provide it beforehand?
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Exhaustive Attack
• A.k.a. brute-force attack, is when attacker
tries all passwords (usually in an automated
fashion) until correct one is found
• Difficulty depends on implementation (how
long are passwords, etc)
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Exhaustive Attack
• Example: Assume passwords consist of 26
characters from A-Z, and can have length
from 1 to 8 characters.
– Num. Passwords = 261 + 262 + 263 +…+ 268 = 269 1 ≈ 5 x 1012
– At one password/millisecond, takes 150 years
– At on password/microsecond, takes two months!
• Reasonable time if reward is large enough (e.g.
password protecting file of credit card numbers)
– And expected search times, if all passwords random,
is half these times
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Probable Passwords
• Reduce search space significantly!
• When humans choose words at random, they
tend to choose words that are short, common,
and easy to spell and pronounce.
• Attackers use this info:
– Search passwords from shortest to longest
• All passwords 5 chars or less can be searched in under
4 hours.
• Time given assumes people choose all passwords with
equal probability (e.g. hdlzm, ehlzx are chosen as often
as pizza and beer)
– Spell-checkers often have dictionaries of commonly
used words
• One of these contains 80,000 words. Trying all of
them takes only 80 seconds.
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Passwords Likely for a User
• Usually meaningful to the person
– Name of spouse, child, brother, sister, pet, street
name, or something memorable or familiar
– List of these things is often only a few hundred
entries long at most. Can be checked in under a
second!
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Distribution of Actual Passwords
• 1979 study by Morris and Thompson
– Considered 3,289 passwords
• Results:
–
–
–
–
–
–
–
15 were single ASCII characters
72 were two ASCII characters
464 were three ASCII characters
477 were four alphabetic letters
706 were five alphabetic letters, all same case
605 were six lowercase alphabetic letters
492 were words in dictionaries or lists of names
• Total: 2831 (86%) contained in this list!
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Figures are Not Dated
• 1990: Klein collected appx 15,000 passwords
– 2.7% guessed within 15 minutes, 21% within one
week
• 1992: Spafford collected appx 15,000
passwords
– Average length 6.8 characters
– 28.9% consisted of only lowercase alphabetic
characters
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Figures are Not Dated
• 2002: British online bank Egg finds 50% of
passwords for online banking service were
family members’ names:
–
–
–
–
–
23% children’s names
19% spouse or partner
9% their own name
8% pet names
9% each for celebrity and soccer star’s names
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Still Worse
• 1998: Knight and Hartley report appx 35% of
passwords derived from syllables and initials of account
owner’s name.
• Several articles claim that God, sex, love, and money
are four most common passwords
• Lists of common passwords posted online
– http://www.geodsoft.com/howto/password/common.htm
– http://www.phenoelit.de/dpl/dpl.html
– Also sites that post dictionaries of phrases, science fiction
characters, places, mythological names, Chinese words,
Yiddish words, and several other specialized lists
• Sysadmin utilities such as SATAN, COPS, and Crack
allow administrators to check for weak passwords.
They also allow attackers to do the same.
• Changing letters to numbers (e.g., 0 for letter O, 1 for
lowercase L, etc): been done, and the attackers know it.
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Knight and Hartley 12 Password
Guessing Steps
•
•
•
•
•
•
•
•
•
•
•
•
No password
The same as the user ID
Is, or is derived from, the user name
Common word list (e.g., password, secret) plus common
names and patterns (e.g., asdfg, aaaaaa)
Short college dictionary
Complete English word list
Common non-English language dictionaries
Short college dictionary with capitalizations (PaSsWorD) and
substitutions (0 for O, etc)
Complete English with capitalizations and substitutions
Common non-English dictionaries with capitalizations and
substitutions
Brute force, lowercase alphabetic characters
Brute force, full character set
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Plaintext System Password List
• Not a good idea
• Even if protected via access control (e.g., only
OS level functions can access it) it’s not good
– Many OS functions never need to read the file, and
opening it to all OS functions means that if even one
of these functions is compromised, password list is
compromised as well
• System backups often lack protection
mechanisms (physical security and access
control to the backup tapes themselves are
only security for these).
• Password file is stored on a disk, so anyone
who can overcome file restrictions or have
access to disk can obtain password file.
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Encrypted Password File
• Password table entries are encrypted using a one way function
(e.g. hash) and then stored.
• One log in, hash of user password is checked with entry in the
password file.
• A problem: two users who pick same password will notice that
they have the same password hash
• Salt: A small number formed from other info, and appended
to password
– Password + salt is what is hashed
– Salt stored in plaintext. On authentication attempt, OS
appends salt to the password and hashes the extended
password to check against password file.
– E.g., Unix salt is a 12-bit number formed from system
time and process ID.
• Still a good idea to limit access to password file (even if
encrypted)
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Indiscreet Users
• Tape password to side of terminal or write it
down on card just inside top desk drawer
• Users sharing files share passwords “my
password is x, just get the file yourself”
• Verisign (2005) in unscientific poll found that
2/3 of people approached on street
volunteered to disclose their password in
exchange for coupon good for a cup of coffee.
79% admitted they use same password for
multiple systems or sites.
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