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Forensic Investigation
Techniques
STORM Cyber.Care
Assess | Plan | Respond
Full Service offering for Reinsurers, Insurers,
Brokers and Clients.
Assess
Lightweight cyber risk assessments to enable clients to learn
and improve their cyber security and to enable insurers and
reinsurers to manage book risk.
Respond
Delivering a fully coordinated and Integrated Cyber
Incident Response Team (I-CIRT).
Plan
Helping insured clients to create, learn (through training) and
exercise/test their plans in dealing with different types
of cyber incidents in the context of their business.
© Storm Guidance 2019
Forensic Investigation
Techniques
Investigation: Revealing the Picture
Method of
Attack
• Body of Evidence
Was it Stopped
How?
Criminal Theft
Other Criminal
Non-Criminal
Error
Why?
Detected?
Compromised?
When?
Controls Failed
Affected
Systems
Location
• Organisation
• 3rd Party
• Staff Home
• Mobile
• Attacker Location
Data Went
Where?
Was Targeted
• Staff Involved
• 3rd Parties Involved
Was
Responsible
• Attacker type
• Location/Identity
Who?
Was
Compromised
• Incident Type
Was/is Potential
Impact
• Severity
• Priority
What?
Technical response objectives
 Triage of breach
 Analysis of the incident “Indicators of Compromise” (IoC)
 Halt the spread or worsening of the compromise and limiting the impact
 Digital forensics and testing to investigate the cause and effects of incident/breach
 Recover when needed:
– Clear existing environment or establish new environment in preparation for recovery
– Restore all systems and business data to operational readiness
 Implement more effective controls and make whole any compensating controls
 Post-incident reporting and analysis
3
Incident Stats
4
 129 incidents in last 12 months: range of types and size of victim org.
 Mailbox hijacking – BEC
– Significant Rise in targeted fraud
 Ransomware/Extortion
 Advanced malware incidents increasing
 Data Theft: PII and other digital assets
 Diverse causes and types of incident – some not actual breaches
 Range of Impacts: sometimes significant loss – increasing BI
 Increasing regulator scrutiny: GDPR – 72 hour window
4
The BEC Analysis Challenge
5
 Business Email Compromise an extremely simple attack
 Starts with Phishing; usually from trusted parties, aim: steal login credentials
 Attackers use credentials to hijack users online mailbox(es)
 Mailbox rules are often used to hide activity and assist the criminals
 Main aim of the hijack is to detect and manipulate payment instructions
 In the process, (often) significant PII is accessible and downloaded
 Downstream risk of attacker extortion with threat to release news of breach
 GDPR/MU DPA requires notification of all data subjects who may be
at ‘high risk’ as a result of the data breach
 As part of our investigation we need to inform the client about:
 Sensitive data which may put data subjects at ‘high risk’ e.g. fraud & ID theft
 Identify all data subjects to inform the notification activity
5
6
 Mailbox data is highly unstructured and not easily searchable for PII
 Often there are many Gigabytes of data from many years of activity
 It is not just messages & attachments…
 Calendar entries (with attachments), Tasks & Contacts
 Files (OneDrive & SharePoint)
 Automated searching is used extensively with our forensic toolset and without
losing the overall evidential integrity often risked with e-Discovery tools
 Often, sensitive data is contained within scanned documents (images) which
cannot be reliably searched.
 Scanned documents include passports, driving licenses, ID records,
agreements, bank statements etc.
6
The BEC Analysis Challenge
The BEC Analysis Challenge
The BEC Analysis Steps
1. Extract mailbox(es) into standard file format for forensics tool
2. Load the mailbox(es) into the forensics tool and perform indexing
function
3. Run initial analysis report and share results
4. Initiate build of spreadsheet tool
5. Arrange search terms (more of which may be added dependent
on findings during analysis)
6. Run search terms and enhance with Boolean expressions where
necessary to exclude FNs and reduce FPs
7. Manually verify results on searches returning key sensitive
information including image files of note
8. De-duplicate
9. Report
10. Carve out items of interest for legal consideration
7
The BEC Analysis Challenge
8
 Considerable manual effort is therefore needed to:
 Contextualise email discussion threads to determine risk
 Read and classify image files
 Dismiss false positives generated by automated searches
 Carve out message attachments for review by legal specialists
 Record data found against data subjects to assess risk in the aggregate
 create a register of the affected data subjects so as to aid legal advice
around risk, and enable suitable notification responses if required.
8
The BEC Analysis Challenge
9
The BEC Analysis Challenge
10
De-duplication
Findings totals
STORM BEC Analysis Process
1. Request Client complete Mailbox Analysis Questionnaire for each mailbox
2. Assist Client in advice on export
3. Receive the Mailbox in PST format
4. Verify the PST (PST viewer - check that it opens, check date range to
confirm all mailbox or incomplete/limited extraction
5. Load into e-Discovery platform & run indexing process
6. Run Insight report: Share with client and discuss estimated time to complete
7. Run searches (Pre-defined Search Lists)
11
STORM BEC Analysis Process
8. Need to select search terms (within selected lists) to maximise
accuracy and minimise false positives - called ‘alignment’.
9. Randomly select results and check alignment.
10. Make modifications to improve the alignment
11. Grade and group search term results into Batches for analysis
(200-300 search results per batch).
12. Results of batch analysis is transcribed into the DDS spreadsheet.
13. De-duplicate the DDS spreadsheet
14. Design and execute the Notification exercise driven from the DDS
12
What to Expect in 2020
 Further rise in reported incidents
 Specific rise in mailbox hijacking – BEC
– Unless Microsoft make Multi-Factor Authentication (MFA) mandatory
 Further advanced Ransomware attacks with data exfiltration
 Extortion from historic Data Thefts – threat intel important
 Rise in sophisticated malware (called RAT) assisted frauds
 Continued focus on social engineering scams
 Renewed drive to reduce fraud opportunities
– Banks to include account name in transaction integrity checks
– Better email analysis and mailbox threat/phishing detection
13
© Storm Guidance 2019
Neil Hare-Brown
Thank you

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4. Forensic Investigation Techniques By Neil Hare Brown.pptx

  • 2. STORM Cyber.Care Assess | Plan | Respond Full Service offering for Reinsurers, Insurers, Brokers and Clients. Assess Lightweight cyber risk assessments to enable clients to learn and improve their cyber security and to enable insurers and reinsurers to manage book risk. Respond Delivering a fully coordinated and Integrated Cyber Incident Response Team (I-CIRT). Plan Helping insured clients to create, learn (through training) and exercise/test their plans in dealing with different types of cyber incidents in the context of their business. © Storm Guidance 2019 Forensic Investigation Techniques
  • 3. Investigation: Revealing the Picture Method of Attack • Body of Evidence Was it Stopped How? Criminal Theft Other Criminal Non-Criminal Error Why? Detected? Compromised? When? Controls Failed Affected Systems Location • Organisation • 3rd Party • Staff Home • Mobile • Attacker Location Data Went Where? Was Targeted • Staff Involved • 3rd Parties Involved Was Responsible • Attacker type • Location/Identity Who? Was Compromised • Incident Type Was/is Potential Impact • Severity • Priority What?
  • 4. Technical response objectives  Triage of breach  Analysis of the incident “Indicators of Compromise” (IoC)  Halt the spread or worsening of the compromise and limiting the impact  Digital forensics and testing to investigate the cause and effects of incident/breach  Recover when needed: – Clear existing environment or establish new environment in preparation for recovery – Restore all systems and business data to operational readiness  Implement more effective controls and make whole any compensating controls  Post-incident reporting and analysis 3
  • 5. Incident Stats 4  129 incidents in last 12 months: range of types and size of victim org.  Mailbox hijacking – BEC – Significant Rise in targeted fraud  Ransomware/Extortion  Advanced malware incidents increasing  Data Theft: PII and other digital assets  Diverse causes and types of incident – some not actual breaches  Range of Impacts: sometimes significant loss – increasing BI  Increasing regulator scrutiny: GDPR – 72 hour window 4
  • 6. The BEC Analysis Challenge 5  Business Email Compromise an extremely simple attack  Starts with Phishing; usually from trusted parties, aim: steal login credentials  Attackers use credentials to hijack users online mailbox(es)  Mailbox rules are often used to hide activity and assist the criminals  Main aim of the hijack is to detect and manipulate payment instructions  In the process, (often) significant PII is accessible and downloaded  Downstream risk of attacker extortion with threat to release news of breach  GDPR/MU DPA requires notification of all data subjects who may be at ‘high risk’ as a result of the data breach  As part of our investigation we need to inform the client about:  Sensitive data which may put data subjects at ‘high risk’ e.g. fraud & ID theft  Identify all data subjects to inform the notification activity 5
  • 7. 6  Mailbox data is highly unstructured and not easily searchable for PII  Often there are many Gigabytes of data from many years of activity  It is not just messages & attachments…  Calendar entries (with attachments), Tasks & Contacts  Files (OneDrive & SharePoint)  Automated searching is used extensively with our forensic toolset and without losing the overall evidential integrity often risked with e-Discovery tools  Often, sensitive data is contained within scanned documents (images) which cannot be reliably searched.  Scanned documents include passports, driving licenses, ID records, agreements, bank statements etc. 6 The BEC Analysis Challenge
  • 8. The BEC Analysis Challenge The BEC Analysis Steps 1. Extract mailbox(es) into standard file format for forensics tool 2. Load the mailbox(es) into the forensics tool and perform indexing function 3. Run initial analysis report and share results 4. Initiate build of spreadsheet tool 5. Arrange search terms (more of which may be added dependent on findings during analysis) 6. Run search terms and enhance with Boolean expressions where necessary to exclude FNs and reduce FPs 7. Manually verify results on searches returning key sensitive information including image files of note 8. De-duplicate 9. Report 10. Carve out items of interest for legal consideration 7
  • 9. The BEC Analysis Challenge 8  Considerable manual effort is therefore needed to:  Contextualise email discussion threads to determine risk  Read and classify image files  Dismiss false positives generated by automated searches  Carve out message attachments for review by legal specialists  Record data found against data subjects to assess risk in the aggregate  create a register of the affected data subjects so as to aid legal advice around risk, and enable suitable notification responses if required. 8
  • 10. The BEC Analysis Challenge 9
  • 11. The BEC Analysis Challenge 10 De-duplication Findings totals
  • 12. STORM BEC Analysis Process 1. Request Client complete Mailbox Analysis Questionnaire for each mailbox 2. Assist Client in advice on export 3. Receive the Mailbox in PST format 4. Verify the PST (PST viewer - check that it opens, check date range to confirm all mailbox or incomplete/limited extraction 5. Load into e-Discovery platform & run indexing process 6. Run Insight report: Share with client and discuss estimated time to complete 7. Run searches (Pre-defined Search Lists) 11
  • 13. STORM BEC Analysis Process 8. Need to select search terms (within selected lists) to maximise accuracy and minimise false positives - called ‘alignment’. 9. Randomly select results and check alignment. 10. Make modifications to improve the alignment 11. Grade and group search term results into Batches for analysis (200-300 search results per batch). 12. Results of batch analysis is transcribed into the DDS spreadsheet. 13. De-duplicate the DDS spreadsheet 14. Design and execute the Notification exercise driven from the DDS 12
  • 14. What to Expect in 2020  Further rise in reported incidents  Specific rise in mailbox hijacking – BEC – Unless Microsoft make Multi-Factor Authentication (MFA) mandatory  Further advanced Ransomware attacks with data exfiltration  Extortion from historic Data Thefts – threat intel important  Rise in sophisticated malware (called RAT) assisted frauds  Continued focus on social engineering scams  Renewed drive to reduce fraud opportunities – Banks to include account name in transaction integrity checks – Better email analysis and mailbox threat/phishing detection 13
  • 15. © Storm Guidance 2019 Neil Hare-Brown Thank you