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Solving Data Breach Points of Egress with Sophisticated Analysis. Christopher Andrews, CFCE, EnCE Director, Kroll Advisory Solutions. About the speaker.
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Solving Data Breach Points of Egress with Sophisticated Analysis Christopher Andrews, CFCE, EnCE Director, Kroll Advisory Solutions
About the speaker • Christopher Andrews is a Director for Kroll Advisory Solutions, formerly with Kroll Ontrack, the recognized worldwide leader in the computer forensics industry. • Mr. Andrews conducts investigations involving the analysis of electronic media for litigation and is often called upon to provide expert testimony. • Previously, Mr. Andrews was a Special Agent with the Northern California Computer Crimes Task Force. He assisted more than 40 law enforcement agencies with the seizure and forensic examination of computers and related storage media. • Mr. Andrews is a member of many professional organizations, including IACIS and HTCIA and has been a speaker at several national conferences. He has also authored numerous articles.
Agenda • A recent case study • Witness interviews • Basic forensic analysis of workstations, servers and volatile memory for evidence of unauthorized access • Log analysis • Timeline analysis • Exfiltration of data
Day One - Discovery • Victim is a health care provider • Victim customers call into help desk – unable to access the network • Victim IT finds unauthorized access to the network • Suspicious internal data traffic • Evidence of rootkits, remote access, and malware found by IT department
Day Three – Partnership • Three days since problem initially discovered • Forensics experts brought in to review the problem • Forensic imaging • Log collection • Interviews with IT personnel • Determining history of known vulnerabilities
Investigation - Findings • Proof of installation of malware including secure VPN tunnel used by intruders • Evidence of customized .exe files that can be used to modify the registry and gain shell access • Internet history includes visits to a Russian FTP site via intruder’s user profile • Download and launch of a Russian Virtual Server in the victim environment! • Server was leased an IP address by the victim servers without triggering any alarms
Investigation - Decision • Victim password HASHES located on a Russian server • Over 2,000 files containing PHI had last accessed dates post-intrusion • These files were accessible, and the possibility that PHI was transferred could not be ruled out • Transaction logs that might establish exfiltration of data were destroyed/missing
Response and Evidence Gathering • Goal: • Identify systems that are under attack or require analysis • Identify and document population of internal investigations and analysis • Develop a protocol / collect volatile and static evidence • Preserve other forms of data and information
Identify and Interview Key Custodians, IT, and Other Witnesses • Take your time. Plan these out. This is a very important step. • Okay to gain general info in a group setting, but best to interview key witnesses individually. • Not an interrogation. Treat witnesses like victims of a crime BUT do not say anything that might get you in trouble later if the witness turns out to be a suspect! • Take lots of notes. Audio/video record?
Identify and Interview Key Custodians, IT, and Other Witnesses • Ideally, have a second investigator there to take notes and to rotate questions. • Get the witnesses contact information and ask if OK to follow-up later. • Leave the witness your card and tell them OK to contact you if they think of anything else. • Transcribe notes soon after interview. Note any follow-up questions.
Basic forensic analysis of workstations, servers and volatile memory for evidence of unauthorized access
Back in the Lab – Some Basic First Steps • Start a tracking sheet: list all media, tasks to perform, notable findings, search terms (IP addresses, URLs, etc.) • Recover deleted files • Run scans for known and suspected malware using specialized malware scanning applications and HASHing • Run keyword searches on all data (active, deleted, slack, unallocated) for common terms associated with malware, password stealing tools, and other intrusion artifacts
Windows Basics • Parse Registry files for some basic items: • Auto-run lists, MRU lists, IP addresses leased, unauthorized software, unauthorized user profiles, FTP lists, Typed URLS, Jump Lists, Drive mappings, MUICache, ShellBags, UserAssist, Compression tools used (WinZIP, WinRAR), etc. • Parse Event logs, IIS, AV and other logs • Parse Prefetch files (if applicable) • Parse shell link files and Internet History • Look for unauthorized user folders and content
Linux Basics • Parse syslogs, bash history, and other logs • Once notable dates are identified, run searches against unallocated for missing log records • Look for unauthorized user folders and content • passwd, shadow, and group file review
RAM Basics • Parse for running processes • Parse for registry keys • Parse for drivers • Parse for open files • Run searches for known terms such as suspicious IP addresses/URLs • Other items (file carving?)
Malware • ID as much as possible. Is it known malware? • Reverse-Engineer the malware if possible • Are there unique findings that you can use as part of a search term? • Example: Hacker Defender / Hamachi • Does the malware even allow for the kind of activity that the victim is worried about? • Zeus variants, for example, will typically not allow remote access/data exfiltration other than typed URLS/passwords
Malware • Example: unauthorized activity on a server in our scenario on November 22, 2011 at 0921 hours • Symantec EndPoint logs show the following activity from the suspect user profile • Changed value 'HKLM\SOFTWARE\Intel\LANDesk\VirusProtect6\CurrentVersion\Storages\Filesystem\RealTimeScan\OnOff' from '1' to '0‘ • A few hours later the following files are ‘created’ on the same server.
Too Much Data! • Various kinds of log findings – consider software to aggregate them all together • Generally, we want to normalize the log data • Free tools like Splunk, DAD, many others • Take into account date/time differences • Focus on known suspicious findings such as IP addresses, dates/times of suspected intrusion, etc. • DB are somewhat unique – may require special queries to get the logs you need
Art and Science • Aggregate your CF findings into one location, like a spreadsheet or database • Look for common dates such as created/generated, last written/modified, last accessed/opened, last run, etc. • Use some automated tools to assist such as the SIFT workstation • Be careful with overly simple interpretation! • Last Accessed – not so good in most cases • Don’t assume dates from malware and unauthorized access are 100% accurate!
Two Basic Ways to Approach This Topic • Top-down approach: Start with all data and based on the CF findings start to figure out what the suspect might have accessed • Requires a lot of review and you could end up with a lot of non-relevant data • Findings can be inconclusive if Windows profiles were hijacked • Bottom-up approach: Limit the review to known data that the VM has identified as important • Examples would be PHI within an SQL database, PII records in an Excel file, etc.
Direct Evidence or Circumstantial? • The more findings the better. More machines = more evidence = PATTERNS • Review all CF findings, logs, etc. Run new searches as needed. Example: IP address lists typically get longer… • Consider “Online Analytics”. You might find “the smoking gun”! • Can file(s) be ruled out? Example: consider file system metadata. Is Last Accessed an accurate date? If so can notable files be ruled out?
Notification/Numbers of PHI/PII Records – 3 approaches • Known records based on solid CF findings • Extrapolated records based on solid CF findings + logs and other data • Theoretical records based on means, motive, opportunity • Top-down? Can we eliminate some records? • Bottom-up? Do we low-ball based on CF findings and hope that we are right?