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Denial of Service. Denial of Service Attacks Unlike other forms of computer attacks, goal isnt access or theft of information or services The goal is.

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Presentation on theme: "Denial of Service. Denial of Service Attacks Unlike other forms of computer attacks, goal isnt access or theft of information or services The goal is."— Presentation transcript:

1 Denial of Service

2 Denial of Service Attacks Unlike other forms of computer attacks, goal isnt access or theft of information or services The goal is to stop the service from operating – 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

3 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

4 High-level Attack Categorization Floods Congestion control exploits Unexpected header values Invalid content Invalid fragments Large packets Impersonation attacks

5 Simple Denial of Service 5

6 One machine tries to bring down another machine There is a fundamental problem for the attacker: – 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

7 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 its 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

8 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

9 Distributed Denial-of-Service

10 Typical Attack Modus Operandi

11 Is DDoS a Real Problem? Yes, attacks happen every day – One study reported ~4,000 per week 1 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

12 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 article. Originally provided by Arbor Networks

13 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

14 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

15 Potential Effects of DDoS Attacks Most (if not all) sites could be rendered non- operational 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

16 Who Is Vulnerable? Everyone connected to the Internet can be attacked Everyone who uses Internet for crucial operations can suffer damages

17 But My Machines Are Well Secured! 17 Doesnt matter! The problem isnt your vulnerability, its everyone elses

18 But I Have a Firewall! Doesnt matter! Either the attacker slips his traffic into legitimate traffic Or he attacks the firewall

19 But I Use a VPN! Doesnt matter! The attacker can fill your tunnel with garbage Sure, youll detect it and discard it... But youll be so busy doing so that youll have no time for your real work

20 But Im Heavily Provisioned Doesnt matter! The attacker can probably get enough resources to overcome any level of resources you buy

21 Attack Toolkits Widely available on the net – Easily downloaded along with source code – Easily deployed and used Automated code for: – Scanning – detection of vulnerable machines – Exploit – breaking into the machine – Infection – placing the attack code Rootkits – Hide the attack code – Restart the attack code – Keep open backdoors for attacker access DDoS attack code

22 DDoS Attack Code Attacker can customize: – Type of attack 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

23 Implications Of Attack Toolkits You dont 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

24 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 (well- formed) application traffic Social-network recruitment

25 How Come We Have DDoS? Natural consequence of the way Internet is organized – Best effort service means routers dont 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

26 There Are Still No Strong Defenses Against DDoS You can make yourself harder to attack But you cant make it impossible And, if you havent made it hard enough, theres not much you can do when you are attacked – There are no patches to apply – There is no switch to turn – There might be no filtering rule to apply – Grin and bear it

27 Why Is DDoS Hard to Solve? 1.A simple form of attack 2.Designed to prey on the Internets strengths 3.Easy availability of attack machines 4.Attack can look like normal traffic 5.Lack of Internet enforcement tools 6.Hard to get cooperation from others 7.Effective solutions hard to deploy

28 1. Simplicity Of Attack Basically, just send someone a lot of traffic More complicated versions can add refinements, but thats 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

29 2. Preys On Internets Strengths The Internet was designed to deliver lots of traffic – 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

30 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

31 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 – Particularly if you dont care which 1,000 Botnets numbering hundreds of thousands of hosts have been discovered

32 Cant We Fix These Vulnerabilities? DDoS attacks dont really harm the attacking machines Many people dont 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

33 4. Attacks Resemble Normal Traffic A DDoS attack can consist of vast number of requests for a web servers 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 – In principle – Not often done because dumb attacks work so well

34 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 theyre 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

35 What Is the Internet Lacking? No validation of IP source address No enforcement of amount of resources used No method of tracking attack flows – 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

36 6. Poor Cooperation In the Internet Its 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

37 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 – 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

38 Resource Limitations Dont allow an individual attack machine to use many of a targets resources Requires: – 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

39 Hiding From the Attacker Make it hard for anyone but legitimate clients to deliver messages at all E.g., keep your machines 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, its fragile – Some such approaches dont require secrecy

40 Resource Multiplication 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

41 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 arent spoofed – Tracing may be possible even if they are spoofed May not have ability/authority to do anything once youve found the attack machines Not too helpful if attacker has a vast supply of machines

42 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: – What do you drop? Good solutions drop all (and only) attack traffic Less good solutions drop some (or all) of everything

43 Filtering Vs. Rate Limiting Filtering drops packets with particular characteristics – 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 – 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

44 Where Do You Filter? Near the target? Near the source? In the network core? In multiple places?

45 Filtering Location Choices Near target Near source In core

46 Filtering Location Choices Near target – Easier to detect attack – Sees everything – May be hard to prevent collateral damage – May be hard to handle attack volume Near source In core

47 Filtering Location Choices Near target Near source – May be hard to detect attack – Doesnt see everything – Easier to prevent collateral damage – Easier to handle attack volume In core

48 Filtering Location Choices Near target Near source In core – Easier to handle attack volume – Sees everything (with sufficient deployment) – May be hard to prevent collateral damage – May be hard to detect attack

49 How Do You Detect Attacks? Have database of attack signatures Detect anomalous behavior – By measuring some parameters for a long time and setting a baseline Detecting when their values are abnormally high – By defining which behavior must be obeyed starting from some protocol specification

50 How Do You Filter? Devise filters that encompass most of anomalous traffic Drop everything but give priority to legitimate- looking traffic – It has some parameter values – It has certain behavior

51 DDoS Defense Challenges 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

52 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

53 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

54 Small-Packet Floods Overwhelm routers – Create a lot of pps – Exhaust CPU – Most routers cant handle full bandwidths load of small packets No real solution, must filter packets somehow to reduce router load

55 Shrew Attack Periodically slam the victim with short, high-volume pulses – Lead to congestion drops on clients 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

56 Flash-Crowd Attack Generate legitimate application traffic to the victim – 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

57 Reflector Attack Generate service requests to public servers spoofing the victims 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

58 Sample Research Defenses Pushback Traceback SOS Proof-of-work systems Human behavior modeling

59 Pushback 1 Goal: Preferentially drop attack traffic to relieve congestion Local ACC: Enable core routers to respond to congestion locally by: – 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 1 Controlling high bandwidth aggregates in the network, Mahajan, Bellovin, Floyd, Paxson, Shenker, ACM CCR, July 2002

60 Can it Work? Even a few core routers are able to control high- volume attacks Separation of traffic aggregates improves current situation – 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

61 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 61

62 Traceback 1 Goal: locate the agent machines Each packet header may carry a mark, containing: – 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 1 Practical network support for IP Traceback, Savage, Wetherall, Karlin, Anderson, ACM SIGCOMM 2000

63 Traceback and IP Spoofing Traceback does nothing to stop DDoS attacks It only identifies attackers true locations – 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

64 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: – Path information cannot be used for legal purposes – Routers close to the sources can efficiently block attack traffic, minimizing collateral damage

65 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

66 SOS 1 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 66 1 SOS: Secure Overlay Services, Keromytis, Misra, Rubensteain, ACM SIGCOMM 2002

67 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 users 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 – Secret servlets 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 67

68 Can It Work? SOS successfully protects communication with a private server: – 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 68

69 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 69

70 Client Puzzles 1 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 70 1 Client puzzles: A cryptographic countermeasure against connection depletion attacks, Juels, Brainard, NDSS 1999

71 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 71

72 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) 72

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