Denial of Service
Denial of Service Attacks
• Unlike other forms of computer attacks, goal
isn’t access or theft of information or services
• The goal is to stop the service from operating
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To deny service to legitimate users
Slowing down may be good enough
• This is usually a temporary effect that passes
as soon as the attack stops
How Can a Service Be Denied?
• Lots of ways
– Crash the machine
– Or put it into an infinite loop
– Crash routers on the path to the machine
– Use up a key machine resource
– Use up a key network resource
– Deny another service needed for this one (DNS)
• Using up resources is the most common
approach
High-level Attack Categorization
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Floods
Congestion control exploits
Unexpected header values
Invalid content
Invalid fragments
Large packets
Impersonation attacks
Simple Denial of Service
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Simple Denial of Service
• One machine tries to bring down another
machine
• There is a fundamental problem for the
attacker:
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The attack machine must be “more powerful”
than the target machine to overload it OR
Attacker uses approaches other than flooding
• The target machine might be a powerful
server
Denial of Service and Asymmetry
• Sometimes generating a request is cheaper
than formulating a response e.g. sending a
bogus packet is cheaper than decrypting this
packet and checking that it’s bogus
• If so, one attack machine can generate a lot of
requests, and effectively multiply its power
• Not always possible to achieve this asymmetry
• This is called amplification effect
DDoS “Solves” That Problem
• Use multiple machines to generate the
workload
• For any server of fixed power, enough attack
machines working together can overload it
• Enlist lots of machines and coordinate their
attack on a single machine
Distributed Denial-of-Service
Typical Attack Modus Operandi
Is DDoS a Real Problem?
• Yes, attacks happen every day
–
One study reported ~4,000 per week1
• On a wide variety of targets
• Tend to be highly successful
• There are very few mechanisms that can stop
certain attacks
• There have been successful attacks on major
commercial sites
1”Inferring
Internet Denial of Service Activity,” Moore, Voelker, and Savage, Usenix Security Symposium, 2002
DDoS on Twitter
• August 2009, hours-long service outage
– 44 million users affected
• At the same time Facebook, LiveJournal,
YouTube and Blogger were under attack
– Only some users experienced an outage
• Real target: a Georgian blogger
Image borrowed
from Wired.com
article. Originally
provided by Arbor
Networks
DDoS on Mastercard and Visa
• December 2010
• Parts of services went down briefly
• Attack launched by a group of vigilantes called
Anonymous
– Bots recruited through social engineering
– Directed to download DDoS software and take
instructions from a master
– Motivation: Payback to services that cut their support
of WikiLeaks after their founder was arrested on
unrelated charges
• Several other services affected
DDoS on US Banks
• September 2012
• BofA, Chase and Wells Fargo were among
those attacked
– Services were interrupted
• Attack claimed to be launched by a Muslim
group Izz ad-Din al Qassam Cyber Fighters
– Motivation: outrage about “Innocence of
Muslims” movie
Potential Effects of DDoS Attacks
• Most (if not all) sites could be rendered nonoperational
• The Internet could be largely flooded with
garbage traffic
• Essentially, the Internet could grind to a halt
–
In the face of a very large attack
• Almost any site could be put out of business
–
With a moderate sized attack
Who Is Vulnerable?
• Everyone connected to the Internet can be
attacked
• Everyone who uses Internet for crucial
operations can suffer damages
But My Machines Are Well Secured!
Doesn’t matter!
The problem isn’t your vulnerability,
it’s everyone elses’
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But I Have a Firewall!
Doesn’t matter!
Either the attacker slips his traffic into
legitimate traffic
Or he attacks the firewall
But I Use a VPN!
Doesn’t matter!
The attacker can fill your tunnel with garbage
Sure, you’ll detect it and discard it . . .
But you’ll be so busy doing so that you’ll have no time for your
real work
But I’m Heavily Provisioned
Doesn’t matter!
The attacker can probably get enough
resources to overcome any level of
resources you buy
Attack Toolkits
• Widely available on the net
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Easily downloaded along with source code
Easily deployed and used
• Automated code for:
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Scanning – detection of vulnerable machines
Exploit – breaking into the machine
Infection – placing the attack code
• Rootkits
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Hide the attack code
Restart the attack code
Keep open backdoors for attacker access
• DDoS attack code
DDoS Attack Code
• Attacker can customize:
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Type of attack
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•
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UDP flood, ICMP flood, TCP SYN flood, Smurf attack
(broadcast ping flood)
Web server request flood, authentication request flood, DNS
flood
Victim IP address
Duration
Packet size
Source IP spoofing
Dynamics (constant rate or pulsing)
Communication between master and slaves
Implications Of Attack Toolkits
• You don’t need much knowledge or
great skills to perpetrate DDoS
• Toolkits allow unsophisticated users to become DDoS
perpetrators in little time
• DDoS is, unfortunately, a game anyone can play
DDoS Attack Trends
• Attackers follow defense approaches, adjust their
code to bypass defenses
• Use of subnet spoofing defeats ingress filtering
• Use of encryption and decoy packets, IRC or P2P
obscures master-slave communication
• Encryption of attack packets defeats traffic
analysis and signature detection
• Pulsing attacks defeat slow defenses and
traceback
• Flash-crowd attacks generate legitimate (wellformed) application traffic
• Social-network recruitment
How Come We Have DDoS?
• Natural consequence of the way Internet is organized
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Best effort service means routers don’t do much processing
per packet and store no state – they will let anything through
End to end paradigm means routers will enforce no security or
authentication – they will let anything through
• It works real well when both parties play fair
• It creates opportunity for DDoS when one party cheats
There Are Still No Strong
Defenses Against DDoS
• You can make yourself harder to attack
• But you can’t make it impossible
• And, if you haven’t made it hard enough, there’s not
much you can do when you are attacked
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There are no patches to apply
There is no switch to turn
There might be no filtering rule to apply
Grin and bear it
Why Is DDoS Hard to Solve?
1.
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A simple form of attack
Designed to prey on the Internet’s strengths
Easy availability of attack machines
Attack can look like normal traffic
Lack of Internet enforcement tools
Hard to get cooperation from others
Effective solutions hard to deploy
1. Simplicity Of Attack
• Basically, just send someone a lot of traffic
• More complicated versions can add refinements, but
that’s the crux of it
• No need to find new vulnerabilities
• No need to worry about timing, tracing, etc.
• Toolkits are readily available to allow the novice to
perform DDoS
• Even distributed parts are very simple
2. Preys On Internet’s Strengths
• The Internet was designed to deliver lots of traffic
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From lots of places, to lots of places
• DDoS attackers want to deliver lots of traffic from
lots of places to one place
• Any individual packet can look proper to the Internet
• Without sophisticated analysis, even the entire flow
can appear proper
Internet Resource Utilization
• Internet was not designed to monitor resource
utilization
–
Most of it follows first come, first served model
• Many network services work the same way
• And many key underlying mechanisms do, too
• Thus, if a villain can get to the important resources
first, he can often deny them to good users
3. Availability Of Attack Machines
• DDoS is feasible because attackers can enlist many
machines
• Attackers can enlist many machines because many
machines are readily vulnerable
• Not hard to find 1,000 crackable machines on the
Internet
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Particularly if you don’t care which 1,000
• Botnets numbering hundreds of thousands of hosts
have been discovered
Can’t We Fix These Vulnerabilities?
• DDoS attacks don’t really harm the attacking
machines
• Many people don’t protect their machines even
when the attacks can harm them
• Why will they start protecting their machines just to
help others?
• Altruism has not yet proven to be a compelling
argument for for network security
4. Attacks Resemble Normal Traffic
• A DDoS attack can consist of vast number of requests
for a web server’s home page
• No need for attacker to use particular packets or
packet contents
• So neat filtering/signature tools may not help
• Attacker can be arbitrarily sophisticated at mirroring
legitimate traffic
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In principle
Not often done because dumb attacks work so well
5. Lack Of Enforcement Tools
• DDoS attackers have never been caught by tracing or
observing attack
• Only by old-fashioned detective work
–
Really, only when they’re dumb enough to boast about
their success
• The Internet offers no help in tracing a single attack
stream, much less multiple ones
• Even if you trace them, a clever attacker leaves no
clues of his identity on those machines
What Is the Internet Lacking?
• No validation of IP source address
• No enforcement of amount of resources used
• No method of tracking attack flows
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Or those controlling attack flows
• No method of assigning responsibility for bad
packets or packet streams
• No mechanism or tools for determining who
corrupted a machine
6. Poor Cooperation In the Internet
• It’s hard to get anyone to help you stop or trace or
prevent an attack
• Even your ISP might not be too cooperative
• Anyone upstream of your ISP is less likely to be
cooperative
–
ISPs more likely to cooperate with each other, though
• Even if cooperation occurs, it occurs at human
timescales
–
The attack might be over by the time you figure out who to
call
7. Effective Solutions Hard To Deploy
• The easiest place to deploy defensive systems is near your
own machine
–
Defenses there might not work well (firewall example)
• There are effective solutions under research
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But they require deployment near attackers or in the Internet
core
Or, worse, in many places
• A working solution is useless without deployment
–
Hard to get anything deployed if deploying site
gets no direct advantage
Resource Limitations
• Don’t allow an individual attack machine to use many
of a target’s resources
• Requires:
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Authentication, or
Making the sender do special work (puzzles)
• Authentication schemes are often expensive for the
receiver
• Existing legitimate senders largely not set up to
handle doing special work
• Can still be overcome with a large enough army of
zombies
Hiding From the Attacker
• Make it hard for anyone but legitimate clients to
deliver messages at all
• E.g., keep your machine’s identity obscure
• A possible solution for some potential targets
–
But not for others, like public web servers
• To the extent that approach relies on secrecy, it’s
fragile
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Some such approaches don’t require secrecy
Resource Multiplication
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As attacker demands more resources, supply them
Essentially, never allow resources to be depleted
Not always possible, usually expensive
Not clear that defender can keep ahead of the attacker
But still a good step against limited attacks
More advanced versions might use
Akamai-like techniques
Trace and Stop Attacks
• Figure out which machines attacks come from
• Go to those machines (or near them) and stop
the attacks
• Tracing is trivial if IP source addresses aren’t
spoofed
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Tracing may be possible even if they are spoofed
• May not have ability/authority to do anything
once you’ve found the attack machines
• Not too helpful if attacker has a vast supply of
machines
Filtering Attack Streams
• The basis for most defensive approaches
• Addresses the core of the problem by limiting the
amount of work presented to target
• Key question is:
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What do you drop?
• Good solutions drop all (and only) attack traffic
• Less good solutions drop some (or all) of everything
Filtering Vs. Rate Limiting
• Filtering drops packets with particular characteristics
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If you get the characteristics right, you do little collateral
damage
At odds with the desire to drop all attack traffic
• Rate limiting drops packets on basis of amount of
traffic
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Can thus assure target is not overwhelmed
But may drop some good traffic
• You can combine them (drop traffic for which you are
sure is suspicious, rate-limit the rest) but you gain a
little
In multiple places?
Where Do You Filter?
Near the
source?
In the network
core?
Near the
target?
Filtering Location Choices
• Near target
• Near source
• In core
Filtering Location Choices
• Near target
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Easier to detect attack
Sees everything
May be hard to prevent collateral damage
May be hard to handle attack volume
• Near source
• In core
Filtering Location Choices
• Near target
• Near source
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May be hard to detect attack
Doesn’t see everything
Easier to prevent collateral damage
Easier to handle attack volume
• In core
Filtering Location Choices
• Near target
• Near source
• In core
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Easier to handle attack volume
Sees everything (with sufficient deployment)
May be hard to prevent collateral damage
May be hard to detect attack
How Do You Detect Attacks?
• Have database of attack signatures
• Detect anomalous behavior
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By measuring some parameters for a long time and setting
a baseline
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Detecting when their values are abnormally high
By defining which behavior must be obeyed starting from
some protocol specification
How Do You Filter?
• Devise filters that encompass most of anomalous
traffic
• Drop everything but give priority to legitimatelooking traffic
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It has some parameter values
It has certain behavior
DDoS Defense Challenges
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Need for a distributed response
Economic and social factors
Lack of detailed attack information
Lack of defense system benchmarks
Difficulty of large-scale testing
Moving target
TCP SYN Flood
• Attacker sends lots of TCP SYN packets
– Victim sends an ack, allocates space in memory
– Attacker never replies
– Goal is to fill up memory before entries time out and get
deleted
• Usually spoofed traffic
– Otherwise patterns may be used for filtering
– OS at the attacker or spoofed address may send RST and
free up memory
TCP SYN Cookies
• Effective defense against TCP SYN flood
– Victim encodes connection information and time in ACK
number
– Must be hard to craft values that get encoded into the
same ACK number – use crypto for encoding
– Memory is only reserved when final ACK comes
• Only the server must change
– But TCP options are not supported
– And lost SYN ACKs are not repeated
Small-Packet Floods
• Overwhelm routers
– Create a lot of pps
– Exhaust CPU
– Most routers can’t handle full bandwidth’s load of small
packets
• No real solution, must filter packets somehow to
reduce router load
Shrew Attack
• Periodically slam the victim with short, high-volume
pulses
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Lead to congestion drops on client’s TCP traffic
TCP backs off
If loss is large back off to 1 MSS per RTT
Attacker slams again after a few RTTs
• Solution requires TCP protocol changes
– Tough to implement since clients must be changed
Flash-Crowd Attack
• Generate legitimate application traffic to the victim
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E.g., DNS requests, Web requests
Usually not spoofed
If enough bots are used no client appears too aggressive
Really hard to filter since both traffic and client behavior
seem identical between attackers and legitimate users
Reflector Attack
• Generate service requests to public servers spoofing
the victim’s IP
– Servers reply back to the victim overwhelming it
– Usually done for UDP and ICMP traffic (TCP SYN flood
would only overwhelm CPU if huge number of packets is
generated)
– Often takes advantage of amplification effect – some
service requests lead to huge replies; this lets attacker
amplify his attack
Sample Research Defenses
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Pushback
Traceback
SOS
Proof-of-work systems
Human behavior modeling
Pushback
1
1”Controlling
high bandwidth aggregates in the network,”
Mahajan, Bellovin, Floyd, Paxson, Shenker, ACM CCR, July 2002
• Goal: Preferentially drop attack traffic to relieve
congestion
• Local ACC: Enable core routers to respond to
congestion locally by:
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Profiling traffic dropped by RED
Identifying high-bandwidth aggregates
Preferentially dropping aggregate traffic to enforce
desired bandwidth limit
• Pushback: A router identifies the upstream
neighbors that forward the aggregate traffic to it,
requests that they deploy rate-limit
Can it Work?
• Even a few core routers are able to control highvolume attacks
• Separation of traffic aggregates improves current
situation
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Only traffic for the victim is dropped
Drops affect a portion containing the attack traffic
• Likely to successfully control the attack, relieving
congestion in the Internet
• Will inflict collateral damage on legitimate traffic
Advantages and Limitations
+ Routers can handle high traffic volumes
+ Deployment at a few core routers can affect
many traffic flows, due to core topology
+ Simple operation, no overhead for routers
+ Pushback minimizes collateral damage by placing
response close to the sources
– Pushback only works in contiguous deployment
– Collateral damage is inflicted by response, whenever
attack is not clearly separable
– Requires modification of existing core routers
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Traceback
1
1“Practical
network support for IP Traceback,” Savage, Wetherall, Karlin, Anderson,
ACM SIGCOMM 2000
• Goal: locate the agent machines
• Each packet header may carry a mark, containing:
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EdgeID (IP addresses of the routers) specifying an edge it has
traversed
The distance from the edge
• Routers mark packets probabilistically
• If a router detects half-marked packet (containing only
one IP address) it will complete the mark
• Victim under attack reconstructs the path from the
marked packets
Traceback and IP Spoofing
• Traceback does nothing to stop DDoS attacks
• It only identifies attackers’ true locations
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Comes to a vicinity of attacker
• If IP spoofing were not possible in the Internet,
traceback would not be necessary
• There are other approaches to filter out spoofed traffic
Can it Work?
• Incrementally deployable, a few disjoint routers can
provide beneficial information
• Moderate router overhead (packet modification)
• A few thousand packets are needed even for long path
reconstruction
• Does not work well for highly distributed attacks
• Path reassembly is computationally demanding, and is
not 100% accurate:
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Path information cannot be used for legal purposes
Routers close to the sources can efficiently block attack traffic,
minimizing collateral damage
Advantages and Limitations
+ Incrementally deployable
+ Effective for non-distributed attacks and for highly
overlapping attack paths
+ Facilitates locating routers close to the sources
– Packet marking incurs overhead at routers, must
be performed at slow path
– Path reassembly is complex and prone to errors
– Reassembly of distributed attack paths is
prohibitively expensive
SOS
1“
1
SOS: Secure Overlay Services,” Keromytis, Misra, Rubensteain, ACM SIGCOMM 2002
• Goal: route only “verified user” traffic to the server,
drop everything else
• Clients use overlay network to reach the server
• Clients are authenticated at the overlay entrance, their
packets are routed to proxies
• Small set of proxies are “approved” to reach the server,
all other traffic is heavily filtered out
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SOS
• User first contacts nodes that can check its legitimacy
and let him access the overlay – access points
• An overlay node uses Chord overlay routing
protocol to send user’s packets to a beacon
• Beacon sends packets to a secret servlet
• Secret servlets tunnel packets to the firewall
• Firewall only lets through packets with an IP
of a secret servlet
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Secret servlet’s identity has to be hidden, because
their source address is a passport for the realm
beyond the firewall
Beacons are nodes that know the identity of secret servlets
• If a node fails, other nodes can take its role
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Can It Work?
• SOS successfully protects communication with a
private server:
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Access points can distinguish legitimate from attack
communications
Overlay protects traffic flow
Firewall drops attack packets
• Redundancy in the overlay and secrecy of the
path to the target provide security against DoS
attacks on SOS
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Advantages And Limitations
+ Ensures communication of “verified user”
with the victim
+ Resilient to overlay node failure
+ Resilient to DoS on the defense system
– Does not work for public service
– Traffic routed through the overlay travels on
suboptimal path
– Brute force attack on links leading to the firewall still
possible
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Client Puzzles
1
1“Client
puzzles: A cryptographic countermeasure against connection depletion attacks,”
Juels, Brainard, NDSS 1999
• Goal: defend against connection depletion attacks
• When under attack:
– Server distributes small cryptographic puzzles to
clients requesting service
– Clients spend resources to solve the puzzles
– Correct solution, submitted on time, leads to state
allocation and connection establishment
– Non-validated connection packets are dropped
• Puzzle generation is stateless
• Client cannot reuse puzzle solutions
• Attacker cannot make use of intercepted packets
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Can It Work?
• Client puzzles guarantee that each client has spent a
certain amount of resources
• Server determines the difficulty of the puzzle
according to its resource consumption
– Effectively server controls its resource consumption
• Protocol is safe against replay or interception attacks
• Other flooding attacks will still work
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Advantages And Limitations
+ Forces the attacker to spend resources, protects
server resources from depletion
+ Attacker can only generate a certain number of
successful connections from one agent machine
+ Low overhead on server
– Requires client modification
– Will not work against highly distributed attacks
– Will not work against bandwidth consumption
attacks (Defense By Offense paper changes this)
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