Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16F6429F953A853F4D6474BE4ED722945332A20FE7FD08A88836189E0F5725CDE47ACA1 |
|
CONTENT
ssdeep
|
3072:NRoIze6lQyThxHgDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAk5:NR6Dw/47g7/tj |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8e2c719ece01cf35 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
6235696969697996 |
|
VISUAL
wHash
|
09003c3c3c3f0fff |
|
VISUAL
colorHash
|
0e201000600 |
|
VISUAL
cropResistant
|
8d9987e6a6a686a6,6235696969697996 |
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 817 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)