CSCD 303 Essential Computer Security Spring 2013

1. CSCD 303Essential Computer SecuritySpring2013 Lecture 4 - Social Engineering1 Phishing Reading:

2. Overview • Social Engineering • Defined • Humans as vulnerabilities • Phishing • What is it? • What does it accomplish • How to recognize it? • Solutions to Phishing

3. Social Engineering • Social EngineeringManipulating or tricking people into divulging private information as opposed to using technical hacking techniques • Or, getting them to use unauthorized devices to compromise themselves

4. Test Case of Human Vulnerabilities • June 2011, Bloomberg published the results of a test conducted by the U.S. Depart. of Homeland Security • To assess the government’s vulnerability to unauthorized system access, • DHS dropped disks and USB drives in parking lots of government agencies and private contractors

5. Test Case of Human Vulnerabilities • Results • 60 % of workers who found devices plugged them into their office computers • When device was imprinted with an official number of installations on office machines skyrocketed to 90 percent http://www.crn.com/blogs-op-ed/channel-voices/232200743/how-to-manage-the-weak-link-in-cybersecurity-humans.htm

6. The Individual User • Users… • Represent the largest install base • Completely lack standards • Cannot be controlled centrally (or otherwise) • Are only predictable in their unpredictability • Cannot be redesigned • Are all of us

7. What Exactly is Phishing? • Define Phishing

8. Phishing Scams Defined • Phishing is type of deception designed to steal your valuable personal data, such as credit card numbers, passwords, account data, or other information • Con artists might send millions of fraudulent e-mail messages that appear to come from Web sites you trust, like your bank or credit card company, and request that you provide personal information.

9. More Phishing Definitions • Spear Phishing– a phishing scam that targets a specific audience above example, but mentions Kansas State University and is sent to K-State email addresses • Scareware - Tries to trick you into responding by using shock, anxiety or threats • “reply with your password now or we’ll shut down your email account tomorrow”

10. Spear-Phishing: Improved Target Selection • Socially aware attacks • Mine social relationships from public data • Phishing email appears to arrive from someone known to victim • Use spoofed identity of trusted organization to gain trust • Urge victims to update or validate their account • Threaten to terminate the account if the victims not reply • Use gift or bonus as a bait • Security promises • Context-aware attacks • “Your bid on eBay has won!” • “The books on your Amazon wish list are on sale!”

11. Phishing Increasing in SophisticationTargeting Your Organization • Spear-phishing targets specific groups or individuals • Type 1 – Uses info about your organization General Patton is retiring next week, click here to say whether you can attend his retirement party

12. Phishing Increasing in SophisticationTargeting Your Organization • Around 40% of people in our experiments at CMU would fall for emails like this (control condition)

13. Phishing Increasing in SophisticationTargeting You Specifically • Type 2 – Uses info specifically about you Social Phishing • Might use information from social networking sites, corporate directories, or publicly available data • Ex. Fake email from friends or co-workers • Ex. Fake videos of you and your friends

14. Phishing Increasing in SophisticationTargeting You Specifically Here’s a video I took of yourposter presentation.

15. Another Example:

16. But wait… WHOIS 210.104.211.21: Location: Korea, Republic Of Even bigger problem: I don’t have an account with US Bank! Images from Anti-Phishing Working Group’s Phishing Archive

17. Spear Phishing Example KSU.edu 17

18. Spear Phishing Example KSU.edu 18

19. Scareware Example 19

20. Scareware Example 20

21. Another Scareware Example 21

22. Another Scareware Example 22

23. Spear phishing scam received by K-Staters, January 2010 If you clicked on the link… 23

24. Malicious link in scam email took you to an exact replica of K-State’s single sign-on web page, hosted on a server in the Netherlands, that steals ID and password if they enter it and click “Sign in” Clicking on “Sign in” then took user to K-State’s home page Note the URL – flushandfloose.nl, which is obviously not k-state.edu 24

25. Fake SSO web page Real SSO web page 25

26. Fake SSO web page – site not secure (http, not https) and hosted in the Netherlands (.nl) Real SSO web page – note “https” 26

27. Fake SSO web page Real SSO web page – Use the eID verification badge to validate 27

28. Result of clicking on eID verification badge on the fake SSO web site, or any site that is not authorized to use the eID and password 28

29. Result of clicking on eID verification badge on a legitimate K-State web site that is authorized to use the eID and password for authentication 29

30. Real K-State FederalCredit Unionweb site Fake K-State Federal Credit Union web site used in spear phishing scam 30

31. History of Phishing • Phreaking + Fishing = Phishing - Phreaking = making phone calls for free back in 70’s - Fishing = Use bait to lure the target • Phishing in 1995 Target: AOL users Purpose: getting account passwords for free time Threat level: low Techniques: Similar names ( www.ao1.com for www.aol.com ), social engineering • Phishing in 2001 Target: Ebayers and major banks Purpose: getting credit card numbers, accounts Threat level: medium Techniques: Same in 1995, keylogger • Phishing in 2007 Target: Paypal, banks, ebay Purpose: bank accounts Threat level: high Techniques: browser vulnerabilities, link obfuscation

32. A bad day phishin’, beats a good day workin’ • 2,000,000 emails are sent • 5% get to the end user – 100,000 (APWG) • 5% click on the phishing link – 5,000 (APWG) • 2% enter data into the phishing site –100 (Gartner) • $1,200 from each person who enters data (FTC) • Potential reward: $120,000 In 2005 David Levi made over $360,000 from 160 people using an eBay Phishing scam

33. How Bad Is Phishing?Consumer Perspective • Estimated ~0.5% of Internet users per year fall for phishing attacks • Conservative $1B+ direct losses a year to consumers Bank accounts, credit card fraud Doesn’t include time wasted on recovery of funds, restoring computers, emotional uncertainty • Growth rate of phishing 30k+ reported unique emails / month 45k+ reported unique sites / month • Social networking sites now major targets

34. How Bad Is Phishing?Perspective of Corporations • Direct damage Loss of sensitive customer data

35. How Bad Is Phishing?Perspective of Corporations • Direct damage Loss of sensitive customer data Loss of intellectual property

36. Why Do People Fall for Phishing? • Phishing has been around for years • How come people still fall for it?

37. Research on PhishingCarnegie Mellon University • Interviewed 40 Internet users including 35 non-experts • Conducted Mental models interviews Mental models included email role play and open ended questions Reference: J Downs, M. Holbrook, and L. Cranor Decision Strategies and Susceptibility to Phishing. In Proc. of the 2006 Symposium On Usable Privacy and Security

38. Research on PhishingCarnegie Mellon University • Only 50% knew the meaning of the term Phishing • 85% were aware of the lock icon • Only 40% knew it was supposed to be there • Only 35% had noticed the https and knew what it means • Only 55% noticed an unexpected or strange URL • Only 55% reported being cautious when asked for sensitive financial info • Few reported being suspicious of being asked for passwords

39. Research on PhishingCarnegie Mellon University • Naïve Evaluation Strategies Most strategies didn't help people in identifying phishing “ This email appears to be for me” “ It's normal to hear from companies you do business with” “ Reputable companies will send emails” • Knowledge of some scams didn't help identify other scams

40. Determining Email Fraud and Protection Measures

41. Today's SolutionsNot so Successful • Anti-phishing filters that rely on blacklists and whitelists Usually not up to date and there are many false positives • Training Websites and posters help some • Spam Filters Don't tend to catch phishing, emails look legitimate

42. More Successful Solutions • Two Research Based Filters, CMU Pilfer Cantina • Pilfer – Looks at other features than email text Number of domains linked to email Links in email to other than the main domain • Cantina – Use Content based approach Creates a fingerprint of a web page Sends fingerprint to search engine Sees if web page is in search results • If yes, then legitimate

43. Detecting Phishing Web Sites • Industry uses blacklists to label phishing sites But blacklists slow to new attacks • Idea: Use search engines Scammers often directly copy web pages But fake pages should have low PageRank on search engines Generate text-based “fingerprint” of web page keywords and send to a search engine Y. Zhang, S. Egelman, L. Cranor, and J. Hong Phinding Phish: Evaluating Anti-Phishing Tools. In NDSS 2007. Y. Zhang, J. Hong, and L. Cranor. CANTINA: A content-based approach to detecting phishing web sites. In WWW 2007. G. Xiang and J. Hong. A Hybrid Phish Detection Approach by Identity Discovery and Keywords Retrieval. In WWW 2009.

44. Human Training • Following slides provide common advice for identifying phishing or fraudulent emails ...

45. Human Training How To Tell If An E-mail Message is Fraudulent Look at few phrases to look for if you think an e-mail message is phishing scam • "Verify your account" 
Businesses should not ask you to send passwords, login names, Social Security numbers, or other personal information through e-mail • If you receive an e-mail from anyone asking you to update your credit card information, do not respond: • This is a phishing scam • "If you don't respond within 48 hours, your account will be closed."
These messages convey a sense of urgency so that you'll respond immediately without thinking

46. Human Training How To Tell If An E-mail Message is Fraudulent "Dear Valued Customer."Phishing e-mail messages are usually sent out in bulk and often do not contain your first or last name "Click the link below to gain access to your account." • HTML-formatted messages can contain links or forms that you can fill out just as you'd fill out a form on a Web site • 
The links that you are urged to click may contain all or part of a real company's name and are usually "masked," meaning that the link you see does not take you to that address but somewhere different, usually a phony Web site.
 • Resting mouse pointer on link reveals the real Web address • String of cryptic numbers looks nothing like the company's Web address, which is a suspicious sign.

47. Human Training How To Tell If An E-mail Message is Fraudulent Con artists also use Uniform Resource Locators (URLs) that resemble the name of a well-known company but are slightly altered by adding, omitting, or transposing letters. For example, the URL "www.microsoft.com" could appear instead as:
 www.micosoft.com 
 www.mircosoft.com 
 www.verify-microsoft.com

48. Human Training How To Tell If An E-mail Message is Fraudulent • Never respond to an email asking for personal information • Always check the site to see if it is secure. Call the phone number if necessary • Never click on the link on the email. Retype the address in a new window • Keep your browser updated • Keep antivirus definitions updated • Use a firewall P.S: Always shred your home documents before discarding them.

49. Human TrainingAnti-Phishing Games • Ok, traditional training doesn't work but .. People like to play games Teach using a game • Results have shown that More people willing to play game than read People are better at identifying phishing after playing the game • Best known is Anti-phishing Phil from CMU http://cups.cs.cmu.edu/antiphishing_phil/

50. Anti-Phishing Phil • A micro-game to teach people not to fall for phish PhishGuru about email, this game about web browser Also based on learning science principles • Try the game! S. Sheng et al. Anti-Phishing Phil: The Design and Evaluation of a Game That Teaches People Not to Fall for Phish. In SOUPS 2007, Pittsburgh, PA, 2007.