Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1685419F9935853F196874BD4F9711A16339610AEFB824B48C3A48AE0FFE2EC9D435C61 |
|
CONTENT
ssdeep
|
3072:umDbhtTa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1DX:DbC7jDw/47g7/t3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9ae075cf0b38de30 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
a8c4786169697904 |
|
VISUAL
wHash
|
007e7e7f7fbc0400 |
|
VISUAL
colorHash
|
3a000000e00 |
|
VISUAL
cropResistant
|
c0c0d0c080808080,a8c4786169697904 |
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 605 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.
Pages with identical visual appearance (based on perceptual hash)