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11
Breaking Fraud & Bot Detection
Solutions
Mayank Dhiman
22
whoami
33
● Defend against bots trying to automate abuse
activities e.g. test credential dumps, scraping
etc.
● Is this activity from a human or a bot?
Bot Detection
Account Take Over Fake Accounts PII / PHI Theft
44
● Defend against fraudulent activities e.g.
manual ATOs, credit card transactions etc.
● Look for anomalies in activity of a given user,
given past activity.
Fraud Detection
55
Motivation
66
Architecture
77
Cloud Deployment
88
Inline Deployment
99
Attacker Goal
● Conduct fraudulent activity
● Automate abuse scripts without getting caught
1010
Threat Model
● Attacker has full control over the browser
● Attacker can craft requests and modify
responses according to the responses from
the server
1111
No client-side
attestation
1212
Attacker can reverse
engineer the entire sensor
1313
Browser Fingerprinting
https://panopticlick.eff.org/
1414
Hardware
- CPU Architecture
- GPU Canvas
Fingerprinting
- Audio Stack
Fingerprinting
Software
- User Agent
- OS Version
Customizations
- Fonts
- Plugins
- Codecs
- Language packs
- Mime types
- Timezone
Browser Fingerprinting
Storage
- LocalStorage
- SessionStorage
Display
- Screen Size
- Color Depth
Misc.
- Floating-point
calculations
- Insert Objects in
DOM
1515
User Tracking
● Mouse Movements
● Key Presses
● Touchpad
● Device Orientation
Timing information along with event type can be used to create a very
accurate picture of what interactions took place on the webpage.
1616
Anti-Tampering
● JavaScript Obfuscation
● XOR based packed code
● Randomize location of JavaScript file to load
1717
Payload
● Payload Encoding (Base64)
● Symmetric Encryption
● Custom Encryption Schemes
1818
No guarantees of correct
execution of JavaScript
1919
Stripping Attack
2020
Stripping Attack
2121
● No check on freshness of payload.
Replay Attacks
2222
Dynamic JS Tokens
● A dynamic token is generated, which is
derived from the timestamp.
● Same logic can be replicated in a script.
2323
Headless Browsers
● Browser without a GUI, often used for
automation and testing
● Either render full JS or run JS in a virtual DOM
2424
No guarantees of
legitimacy of fingerprints
2525
Forging Fingerprints
● FPRANDOM -- Modified browser which
introduces noise in browser fingerprint
● Database of normal fingerprints
https://github.com/plaperdr/fprandom
2626
2727
Forging Fingerprints
2828
Underground Tool
● Anti-Detect* $399 in the underground market
https://krebsonsecurity.com/2015/03/antidetect-helps-thieves-hide-digital-fingerprints/
2929
JavaScript can’t
protect all flows
3030
Device Attestation
● Android’s SafetyNet API
● iOS DeviceCheck API
3131
Architecture
● Recompile mobile app with SDK
● JS → Native Code
● Browser Fingerprint → Device Fingerprint
3232
Device
- Brand
- Model
- IMEI Number
- Device Build
Carrier
- SIM serial no.
- Carrier name
- Phone no. (MSISDN)
Hardware
- CPU Information
- RAM Information
- Camera Information
- Battery Information
- Hardware serial no.
Android Fingerprinting
Storage
- External Capacity
- Internal Capacity
Display
- Screen Resolution
- Screen Orientation
Misc.
- Uptime
- Is Rooted?
- Is Emulator?
Applications
- List of installed apps
- App versions
- List of running
processes
Localisation
- Geolocation
- Country
- Locale
- Timezone
Network
- IP Address
- MAC Address
- Proxy settings
- WiFi SSID
OS
- OS Name
- OS Version
- Kernel Information
- System Fonts
- System Directory
Structure
- BuildID
- Build Fingerprint
3333
What about iOS?
3434
What about API?
3535
Takeaways
● Implementation and architectural issues in
multiple deployments
● Not possible to win the race on web, given no
root-of-trust via browsers
● State of the world in mobile is better
● Getting baseline protection across all flows is
extremely hard
● Inherent privacy issues
3636
Other Issues
● Fraud/Bot detection solutions are also
fingerprintable
3737
Questions?

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