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Security and Privacy in Cloud Computing

Security and Privacy in Cloud Computing. Ragib Hasan Johns Hopkins University en.600.412 Spring 2011. Lecture 2 02/ 07/ 2010. Attack Modeling, and Novel Attack Surfaces. Goal

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Security and Privacy in Cloud Computing

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  1. Security and Privacy in Cloud Computing Ragib HasanJohns Hopkins Universityen.600.412 Spring 2011 Lecture 2 02/07/2010 en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  2. Attack Modeling, and Novel Attack Surfaces Goal Learn the cloud computing threat model by examining the assets, vulnerabilities, entry points, and actors in a cloud Examine a novel topology attack on cloud en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  3. Assignment for next class • Review: Thomas Ristenpart et al., Hey, You, Get Off of My Cloud! Exploring Information Leakage in Third-Party Compute Clouds, proc. ACM CCS 2009. • Format: • Summary: A brief overview of the paper, 1 paragraph (5 / 6 sentences) • Pros: 3 or more issues • Cons: 3 or more issues • Possible improvements: Any possible suggestions to improve the work • Due: 2.59 pm 2/14/2010 • Submission: By email to rhasan7@jhu.edu (text only, no attachments please) (Please use the subject line: Review Assignment 1) en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  4. Threat Model A threat model helps in analyzing a security problem, design mitigation strategies, and evaluate solutions Steps: • Identify attackers, assets, threats and other components • Rank the threats • Choose mitigation strategies • Build solutions based on the strategies en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  5. Threat Model Basic components • Attacker modeling • Choose what attacker to consider • Attacker motivation and capabilities • Assets / Attacker Goals • Vulnerabilities / threats en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  6. Recall: Cloud Computing Stack en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  7. Recall: Cloud Architecture SaaS / PaaS Provider Client Cloud Provider (IaaS) en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  8. Attackers en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  9. Who is the attacker? • Insider? • Malicious employees at client • Malicious employees at Cloud provider • Cloud provider itself • Outsider? • Intruders • Network attackers? en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  10. Attacker Capability: Malicious Insiders • At client • Learn passwords/authentication information • Gain control of the VMs • At cloud provider • Log client communication en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  11. Attacker Capability: Cloud Provider • What? • Can read unencrypted data • Can possibly peek into VMs, or make copies of VMs • Can monitor network communication, application patterns en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  12. Attacker motivation: Cloud Provider • Why? • Gain information about client data • Gain information on client behavior • Sell the information or use itself • Why not? • Cheaper to be honest? • Why? (again) • Third party clouds? en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  13. Attacker Capability: Outside attacker • What? • Listen to network traffic (passive) • Insert malicious traffic (active) • Probe cloud structure (active) • Launch DoS en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  14. Assets en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  15. Threat Model Basic components • Attacker modeling • Choose what attacker to consider • Attacker motivation and capabilities • Assets / Attacker Goals • Vulnerabilities / threats en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  16. Attacker goals: Outside attackers • Intrusion • Network analysis • Man in the middle • Cartography en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  17. Assets (Attacker goals) • Confidentiality: • Data stored in the cloud • Configuration of VMs running on the cloud • Identity of the cloud users • Location of the VMs running client code en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  18. Assets (Attacker goals) • Integrity • Data stored in the cloud • Computations performed on the cloud en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  19. Assets (Attacker goals) • Availability • Cloud infrastructure • SaaS / PaaS en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  20. Threats en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  21. Organizing the threats using STRIDE • Spoofing identity • Tampering with data • Repudiation • Information disclosure • Denial of service • Elevation of privilege en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  22. Typical threats [STRIDE] en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  23. Typical threats (contd.) [STRIDE] en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  24. Summary • A threat model helps in designing appropriate defenses against particular attackers • Your solution and security countermeasures will depend on the particular threat model you want to address en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  25. Mapping/topology Attacks • Lecture Goal • Learn about mapping attacks • Discuss different techniques and mitigation strategies • Analyze the practicality and impact • Reading: • Hey, You, Get Off of My Cloud: Exploring Information Leakage in Third-Party Compute Clouds, Ristenpart et al., CCS 2009 en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  26. Why Cloud Computing brings new threats? Traditional system security mostly means keeping bad guys out The attacker needs to either compromise the auth/access control system, or impersonate existing users en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  27. Why Cloud Computing brings new threats? But clouds allow co-tenancy : Multiple independent users share the same physical infrastructure So, an attacker can legitimately be in the same physical machine as the target en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  28. Challenges for the attacker How to find out where the target is located How to be co-located with the target in the same (physical) machine How to gather information about the target en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  29. Hey, You, Get Off of My Cloud: Exploring Information Leakage in Third-Party Compute Clouds, Ristenpart et al., CCS 2009 • First work on cloud cartography • Attack launched against commercially available “real” cloud (Amazon EC2) • Claims up to 40% success in co-residence with target VM en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  30. Strategy • Map the cloud infrastructure to find where the target is located • Use various heuristics to determine co-residency of two VMs • Launch probe VMs trying to be co-resident with target VMs • Exploit cross-VM leakage to gather info about target en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  31. Threat model Attacker model • Cloud infrastructure provider is trustworthy • Cloud insiders are trustworthy • Attacker is a malicious third party who can legitimately the cloud provider as a client Assets • Confidentiality aware services run on cloud • Availability of services run on cloud en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  32. Tools of the trade • Nmap, hping, wget for network probing • Amazon EC2’s own DNS to map dns names to IPs en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  33. Sidenote: EC2 configuration EC2 uses Xen, with up to 8 instances per physical machine Dom0 is the first instance on the machine, connected to physical adapter All other instances route to external world via dom0 [Figures from Xen Wiki] en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  34. Task 1: Mapping the cloud Reverse engineering the VM placement schemes provides useful heuristics about EC2’s strategy Different availability zones use different IP regions. Each instance has one internal IP and one external IP. Both are static. For example: External IP: 75.101.210.100 External Name: ec2-75-101-210-100.computer-1.amazonaws.com Internal IP: 10.252.146.52 Internal Name: domU-12-31-38-00-8D-C6.computer-1.internal en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  35. Task 1: Mapping the Cloud Finding: same instance type within the same zone= similar IP regions Reverse engineered mapping decision heuristic: A /24 inherits any included sampled instance type. A /24 containing a Dom0 IP address only contains Dom0 IP address. All /24’s between two consecutive Dom0 /24’s inherit the former’s associated type. en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  36. Task #2: Determining co-residence • Co-residence: Check to determine if a given VM is placed in the same physical machine as another VM • Network based check: • Match Dom0 IP addresses, check packet RTT, close IP addresses (within 7, since each machine has 8 VMs at most) • Traceroute provides Dom0 of target • No false positives found during experiments en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  37. Task #3: Making a probe VM co-resident with target VM Brute force scheme • Idea: figure out target’s availability zone and type • Launch many probe instances in the same area • Success rate: 8.4% en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  38. Task #3: Making a probe VM co-resident with target VM Smarter strategy: utilize locality • Idea: VM instances launched right after target are likely to be co-resident with the target • Paper claims 40% success rate en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  39. Task #3: Making a probe VM co-resident with target VM Window of opportunity is quite large, measured in days en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  40. Task #4: Gather leaked information Now that the VM is co-resident with target, what can it do? • Gather information via side channels • Perform DoS en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  41. Task 4.1: Gathering information If VM’s are separated and secure, the best the attacker can do is to gather information • Measure latency of cache loads • Use that to determine • Co-residence • Traffic rates • Keystroke timing en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  42. Mitigation strategies #1: Mapping • Use a randomized scheme to allocate IP addresses • Block some tools (nmap, traceroute) en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  43. Mitigation strategies #2: Co-residence checks • Prevent traceroute (i.e., prevent identification of dom0) en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  44. Mitigation strategies #3: Co-location • Not allow co-residence at all • Beneficial for cloud user • Not efficient for cloud provider en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  45. Mitigation strategies #4: Information leakage • Prevent cache load attacks? en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  46. Discussion • How is the problem different from other attacks? • What’s so special about clouds? en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  47. Discussion Cons • Are the side channels *really* effective? en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

  48. Further Reading Frank Swiderski and Window Snyder , “Threat Modeling “, Microsoft Press, 2004 The STRIDE Threat Model Amazon downplays report highlighting vulnerabilities in its cloud service Hypothetical example described in report much harder to pull off in reality, company saysTechWorld, Oct 29, 2009. http://bit.ly/dvxEZp en.600.412 Spring 2011 Lecture 2 | JHU | Ragib Hasan

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