Your SlideShare is downloading. ×
Attacks Against Captcha Systems - DefCamp 2012
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

Attacks Against Captcha Systems - DefCamp 2012

807

Published on

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
807
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
18
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  • 1. Attacking CAPTCHAs explained Ioan – Carol Plangu
  • 2. Whats a CAPTCHACompletelyAutomatedPublicTuring test to tellComputers andHumansApart
  • 3. Three attack methods Implementation attack Automated recognition Manual labor
  • 4. The implementation attackScenario 1 the image session id can be reused
  • 5. The implementation attackScenario 1 the image session id can be reused id Restricted Captcha page form
  • 6. The implementation attackScenario 2 the number of captcha tests is limited
  • 7. The implementation attackScenario 2 the number of captcha tests is limited we just need to solve them all and store them in a hash table
  • 8. The implementation attackScenario 3 hash of solution sent to client
  • 9. The implementation attackScenario 3 hash of solution sent to client rainbow tables :)
  • 10. Manual laborThere are two options:
  • 11. Pay a bunch of monkeys
  • 12. Or not... XXX Complete this captcha form to continue
  • 13. Automated recognitionWere going to actually reproduce a human response for the given question
  • 14. Can you understand my voice?
  • 15. The sound sample is usually generated
  • 16. Its hard to add noise to thegenerated speech without making it hard for the human
  • 17. But can you read?
  • 18. Sort of.....
  • 19. The most common approach Greedy optimization – reverse engineer everything Character segmentation OCR
  • 20. Possible security measures
  • 21. Possible security measures Funky background image
  • 22. Possible security measures Funky background image − usually can be removed with basic preprocessing
  • 23. Possible security measures Funky background image − usually can be removed with basic preprocessing Text distortions
  • 24. Possible security measures Funky background image − usually can be removed with basic preprocessing Text distortions − modern OCR techniques can beat it
  • 25. Possible security measures Funky background image − usually can be removed with basic preprocessing Text distortions − modern OCR techniques can beat it Anti segmentation measures
  • 26. Beating segmentation
  • 27. Beating segmentation  If a character signature can be extracted from only the vertical signature, character segmentation becomes trivialA Low-cost Attack on a Microsoft CAPTCHA - Jeff Yan, Ahmad Salah El AhmadSchool of Computing Science, Newcastle University, UK
  • 28. Beating segmentationWe can otherwise ignore it!
  • 29. Beating segmentationWe can otherwise ignore it!The following slides are about an experiment about this approach
  • 30. A Monte-Carlo experiment Note: for testing performance, the variance of the characters has been kept to a minimumf(x) → yx in binary( 0 - 2^3000 )y in 10^6
  • 31. Training: − Select one character image at random − Select N black spots − Sort the points for uniqueness − Subtract the first point from all others for position independence − Assign it a weight for each character using the following formula: matched characters count / sample size − Assign it a score (indicates classification quality) selected digit weight / (1 + other digit weights)
  • 32. Recognition: − Make a score map for all points − Select the most appropriate character for each column − Process the resulting string into a 6 digit string
  • 33. An equivalent model input layer linear hidden layer (feature layer) threshold layers softmax layer
  • 34. An equivalent model input layer OCR linear hidden layer (feature layer) without zero penalty == threshold layers No biases for the first layer (avoids the 2*binary - 1 effect) softmax layer
  • 35. Hacking the OCR: To negate the effect the biases, for each image we add random noise in the white areas This will greatly improve the recognition in a noisy image
  • 36. An more powerful model input layer Hacked OCR layer Score map output layer
  • 37. Questions?
  • 38. The demo source is hosted athttps://github.com/theshark08/howtobreakacaptcha01

×