Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C8711273944CDC276263C2C9ADA1F75E66D24306CB4316819BE9839D7ACBDF2CD42154 |
|
CONTENT
ssdeep
|
48:TiwIJFIwBjIwBnIwKSWeBDBwIBOFUTNmTNMMBm8WX9pRkxo58I+lLwe79KiRNAmt:TYwFJ9kDBOBcX9pO0QKiRTP |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b0651e4fb4619ce3 |
|
VISUAL
aHash
|
0000e7c3e70000ff |
|
VISUAL
dHash
|
b27016969632d038 |
|
VISUAL
wHash
|
0000ffc3e700fcff |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
0000000000000000,4d8e969696969696,8405225858382826,083054b2b2b2b430,46f032f171ccd4d4,46f432f171ccd4d4,46f0b27171ccd4c4,100c32b2b04a9484 |
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 52 techniques to evade detection by security scanners and make reverse engineering more difficult.