Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1488261B24218BABE64D6C6E89F2E673B5255D143F9A6014581EDCB38CBC7CC5EE33640 |
|
CONTENT
ssdeep
|
192:lu4t6xkKv8ZZG7zadB3FbVpgStStStStSeucpKpgStStStStSeiEfAmJtG8mDi8O:lxt6xkU12sG8m7FG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
890ce2f3cc81e3f3 |
|
VISUAL
aHash
|
00000000ffffffff |
|
VISUAL
dHash
|
d7f3d7b3b2581a08 |
|
VISUAL
wHash
|
00000000ffffffff |
|
VISUAL
colorHash
|
06000038000 |
|
VISUAL
cropResistant
|
1005555c550400ff,b3b25a1a5a5a122c,f7f7b3f3f7f3f3b3 |
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 212 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)