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manuka project IEEE IA Workshop June 10, 2004
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Agenda Introduction Inspiration to Solution Manuka Use SE Approach Conclusion
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Team Members Seattle University Masters in Computer Science & Software Engineering –Amy Shephard –Christian Seifert –Don Nguyen –Jenks Gibbons –Jose Chavez
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Sponsors –University of Washington Customer: Dave Dittrich –Seattle University Advisor: Barbara Endicott-Popovsky
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Inspiration to Solution
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Inspiration Honeynet Project “Forensic Challenge” –January 15, 2001 –Linux Red Hat 6.2 –Six partitions (1.8GB raw / 170MB gzip) –Time to: Root the box and rootkit (30 minutes) Analyze intrusion and report (30+ hours) –Downloaded thousands of times –Used in first SANS FIRE (Forensics course) http://www.honeynet.org/challenge/index.html
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Application #1 2004 NSF CCLI grant –Highline Community College –Seattle University –University of Washington Computer and Network Forensics Courses Using real compromised honeypot images for labs
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Use in Forensic Course Lab Student boots lab system w/custom Linux bootable CD Chooses which compromised system to analyze Bits loaded to disk, verified Student performs analysis, answers specific questions (which are compared with analysis in database) Lather, rinse, repeat…
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Application #2 Distributed Honeynet using Honeywalls –“Clone” clean honeypot images –Archive compromised honeypot images –Automated honeypot forensics (future)
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Application #3 (future) Distributed Incident Response Toolkit –Customizable (unique) ISO images –Centralized control of analysis –Remote drive acquisition –Asynchronous and semi-automatic operation
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Proposed Solution Use standard x86 hardware (Knoppix) Bit-image copy of clean/compromised systems Provide integrity checking (MD5 hashes) and secure file transfer (SSH) Database storage (compressed) Database search by attribute (e.g., ID#, OS version, CVE #, etc.) Remotely retrieve/install bootable systems Customizable ISO (ala Honeywall) “Customizing ISOs and the Honeynet Project’s Honeywall,” http://staff.washington.edu/dittrich/misc/honeywall/
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Manuka Components –Server Linux, MySQL, Java Automated Manuka database server installation –Client Customized Knoppix CD-ROM (similar to Honeywall) –Password protected –Secure login to database –Secure data transfer
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Manuka Use
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Typical Use Upload clean 1)Install new honeypot 2)Configure vulnerability profile (CVE #N) 3)Reboot w/Manuka CD, ID system, upload Download clean 1)Boot w/Manuka CD 2)Select image and download Upload compromised 1)Boot w/Manuka CD 2)Associate w/original, annotate, upload
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Accessing Manuka –Authentication required for all functionality –Multiple access levels supported
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Upload Installation –Stores an installation in the Manuka database –Clean Image Specify system details Specify installation details Specify vulnerabilities –Compromised Image Associate with existing system Specify installation details
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GZip Compressor Encrypted SSH Tunnel Manuka Database Clean or Compromised System Booted with Knoppix CD File Server : 9999 System Image Metadata System A, BA6512345AFAED2A3D4E11 System B, BA6512345AFAED2A3D4E11 Upload Component MD5 Hash CD33456765673FE23AD4F13 System C, CD33456765673FE23AD4F13
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Download Installation –Writes an installation to the specified drive –Download Installation Specify target, system, and installation details Wait…
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GZip UnCompressor Encrypted SSH Tunnel Manuka Database System to restore (Booted with Knoppix CD) File Server : 9999 Binary Files Location System A, BA651EF45AFAED2A3D4E11 System B, BA6512345AFAED2A3D4E11 Download Component Image 3, CD33456765673FE23AD4F13 Request Binary Images Files MD5 Hash CD33456765673FE23AD4F13 System C, CD33456765673FE23AD4F13
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System Search –Allows targeted access to system information –Search by system metadata –Retrieves all matching systems
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System and Installation Details –Allows access to system data general information vulnerabilities installation details
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Stored Data Management –User updates Operating Systems Operating System Versions –Automatic updates Vulnerabilities
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Software Engineering Approach
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Approach Extreme Programming –Pair programming Methodology –Development of user stories –Estimation/prioritization of user stories –Weekly iteration status meetings –Monthly iteration planning meeting –Working code –Metrics collection
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Methodology Development of user stories Estimation/prioritization of user stories Weekly iteration status meetings Monthly iteration planning meeting Working code Metrics collection
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Project Plan
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The Manuka Times Tasks due Current risks User story status Delayed tasks Acceptance tests results
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Project Website Customer communication Release dissemination Access to –source control –bug tracking –standards –current iteration information
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Conclusion Support tool for setup/imaging of distributed honeypots Support for Hands-on Forensics Lab Exercises Base for Future Honeypot Analysis and IRT toolkit Example of Extreme Programming Concepts in action Questions? http://staff.washington.edu/dittrich/misc/honeywall/
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