SlideShare a Scribd company logo
Nicola CHEMELLO
Computer engineer
OpenText EnCE (since 2009)
Cellebrite CCO (since 2018), CCPA (since 2018),
CCME (since 2019)
Not renewed certifications (ACE, XRY
advanced user, Oxygen)
Securcube CO-FOUNDER
https://www.linkedin.com/in/nicolachemello
Digital Forensics Examiner
SecurCube
Webinar
Series
Ing. Nicola CHEMELLO
www.SecurCube.net
Data Validation
of information resulting from mobile extractions with other elements
Is a mobile phone a trusted source?
The best mobile extraction
● A variety of tools on the
market "profess" to be the best
for specific acquisitions on a
variety of devices
● Cellebrite UFED, MSAB,
Oxygen, … : market leaders
for mobile extractions
● Which is it the most complete?
Is the cloud a trusted source?
Cloud is the place where most of the data is stored: photos, chat backups, documents, … there
are many ones, an investigator should consider to get the data from these places.
Google Timeline
Not only documents, google timeline stores
user’s positions, while using a google account
connected device.
This information should be acquired as well
Download from the cloud
How can you download data from the cloud?
Here there are just a few examples, there are
Many tools that allow you this acquisition
But who entered the data into
the phone / cloud?
The user “itself”
What about anti forensics techniques?
What about fake data received from
someone else?
Fake information
Can someone create a fake document/information in a
phone/cloud and can an investigator support its alibi?
What if I sent a fake sms to my mobile phone spoofing the
victim’s mobile number to create the «why» of my actions?
Google Maps Hack example
99 secondhand smartphones are
transported in a handcart to generate
virtual traffic jam in Google Maps.
Through this activity, it is possible to
turn a green street red which has an
impact in the physical world by
navigating cars on another route to
avoid being stuck in traffic.
#googlemapshacks http://www.simonweckert.com/googlemapshacks.html
The solution:
Data Validation
and Correlation
get/analyze multiple sources that support the same result
Third party data that can support/conflict with the
data extracted from a mobile phone or from the
cloud: Telephone (and telematic) phone records
(CDR – Call Detail Records)
● Historical information that cannot
be canceled / modified
● Created by third parties
● Date / time + location (cell) + type
of traffic carried out + device details
& SIM + ...
Cell Coverage information
Discover where the connected cell tower
has/hasn’s coverage. This helps to understand
what happened
● OpenCellID/public DB
● Theoretical Coverage
● Electromagnetic Coverage Diagaram
(theoretical)
● Real Coverage (Securcube BTS Tracker
HW and the free APP on Google play)
○ Where the signal actually is spread
○ Where a device can actually exchange
communication
Theoretical cell tower coverage and real
coverage obtained from Securcube BTS
tracker survey
Idle cell tower VS
Connected cell
tower
This important consideration has to be checked while
Analyzing connected cell tower.
Real and
Theoretical
Coverage
Consider the green points in
the image in which the cell
tower has coverage, but
outside its theoretical
coverage.
More correlation :
License plates, is the suspect's car moving
with its phone?
● Cameras for verifying
insurance coverage / vehicle
inspection /safety emissions
● Installed in many
municipalities
● Can I figure out who the
suspect's passenger is?
License
Plates
&
Telephone
Records
example
Study where the car was while the
suspect’s mobile phone was
connecting cell towers during its
use
Telephone
Records
&
Mobile
Extractions
Correlating mobile extraction with
CDR you can get something more,
like the used celltowers. It means
the area in which the mobile phone
was while sending that message
Conclusions
● Acquire data from various devices in an optimal way (best practices) is the to
do thing
● Validate the extracted data by considering multiple sources of evidence
○ correlate data with multiple sources, to get a thrustworthy proof of
evidence
○ Point out inconsistencies, and refine the investigative idea
Thank You for the attention
Ing. NicolaCHEMELLO
www.securcube.net

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Data validation using CDR (Call Detail Records) and real cell tower coverage

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  • 2. Nicola CHEMELLO Computer engineer OpenText EnCE (since 2009) Cellebrite CCO (since 2018), CCPA (since 2018), CCME (since 2019) Not renewed certifications (ACE, XRY advanced user, Oxygen) Securcube CO-FOUNDER https://www.linkedin.com/in/nicolachemello Digital Forensics Examiner SecurCube Webinar Series
  • 3. Ing. Nicola CHEMELLO www.SecurCube.net Data Validation of information resulting from mobile extractions with other elements
  • 4. Is a mobile phone a trusted source?
  • 5. The best mobile extraction ● A variety of tools on the market "profess" to be the best for specific acquisitions on a variety of devices ● Cellebrite UFED, MSAB, Oxygen, … : market leaders for mobile extractions ● Which is it the most complete?
  • 6. Is the cloud a trusted source? Cloud is the place where most of the data is stored: photos, chat backups, documents, … there are many ones, an investigator should consider to get the data from these places.
  • 7. Google Timeline Not only documents, google timeline stores user’s positions, while using a google account connected device. This information should be acquired as well
  • 8. Download from the cloud How can you download data from the cloud? Here there are just a few examples, there are Many tools that allow you this acquisition
  • 9. But who entered the data into the phone / cloud? The user “itself” What about anti forensics techniques? What about fake data received from someone else?
  • 10. Fake information Can someone create a fake document/information in a phone/cloud and can an investigator support its alibi? What if I sent a fake sms to my mobile phone spoofing the victim’s mobile number to create the «why» of my actions?
  • 11. Google Maps Hack example 99 secondhand smartphones are transported in a handcart to generate virtual traffic jam in Google Maps. Through this activity, it is possible to turn a green street red which has an impact in the physical world by navigating cars on another route to avoid being stuck in traffic. #googlemapshacks http://www.simonweckert.com/googlemapshacks.html
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  • 13. The solution: Data Validation and Correlation get/analyze multiple sources that support the same result
  • 14. Third party data that can support/conflict with the data extracted from a mobile phone or from the cloud: Telephone (and telematic) phone records (CDR – Call Detail Records) ● Historical information that cannot be canceled / modified ● Created by third parties ● Date / time + location (cell) + type of traffic carried out + device details & SIM + ...
  • 15. Cell Coverage information Discover where the connected cell tower has/hasn’s coverage. This helps to understand what happened ● OpenCellID/public DB ● Theoretical Coverage ● Electromagnetic Coverage Diagaram (theoretical) ● Real Coverage (Securcube BTS Tracker HW and the free APP on Google play) ○ Where the signal actually is spread ○ Where a device can actually exchange communication
  • 16. Theoretical cell tower coverage and real coverage obtained from Securcube BTS tracker survey
  • 17. Idle cell tower VS Connected cell tower This important consideration has to be checked while Analyzing connected cell tower.
  • 18. Real and Theoretical Coverage Consider the green points in the image in which the cell tower has coverage, but outside its theoretical coverage.
  • 19. More correlation : License plates, is the suspect's car moving with its phone? ● Cameras for verifying insurance coverage / vehicle inspection /safety emissions ● Installed in many municipalities ● Can I figure out who the suspect's passenger is?
  • 20. License Plates & Telephone Records example Study where the car was while the suspect’s mobile phone was connecting cell towers during its use
  • 21. Telephone Records & Mobile Extractions Correlating mobile extraction with CDR you can get something more, like the used celltowers. It means the area in which the mobile phone was while sending that message
  • 22. Conclusions ● Acquire data from various devices in an optimal way (best practices) is the to do thing ● Validate the extracted data by considering multiple sources of evidence ○ correlate data with multiple sources, to get a thrustworthy proof of evidence ○ Point out inconsistencies, and refine the investigative idea
  • 23. Thank You for the attention Ing. NicolaCHEMELLO www.securcube.net