Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19F51A4B65520480F72639575EC93B348C0B4E20BC5025D75FB6863FA3BD6EE0C27B120 |
|
CONTENT
ssdeep
|
48:TGiNdjqwlMItrMItUmGGXwghxjf5h3QHOFf+awfcOFf6aPGiXLL:TGTm/imj57h3QugcOxOiXLL |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e86068595979f6a6 |
|
VISUAL
aHash
|
0000ffffffffbf97 |
|
VISUAL
dHash
|
838786bae0475735 |
|
VISUAL
wHash
|
0000e7ffffff0101 |
|
VISUAL
colorHash
|
0e180008000 |
|
VISUAL
cropResistant
|
a6863bf1c8577775,608393939300a082,9dd55454757636b2,494be7e7a7a7261a,6565662a2a2a6a66,aaaececdad2d3517,9959516362666654,e96d569694d6cecc,e2e2cacadada9a98,254545697814968b |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 14 techniques to evade detection by security scanners and make reverse engineering more difficult.
Pages with identical visual appearance (based on perceptual hash)