Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14F728A35A601446707BB89C4F270BF1FB2D6F30F85068555AABD91CA2FC3CB67B61462 |
|
CONTENT
ssdeep
|
192:6cVRcuSAeuJH25PFbFaFCFjMbnFdDUQ0tfnXpyZ:nJeuJH25PFbFaFCFjMbXZ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b232323393d9cdcc |
|
VISUAL
aHash
|
c3c3ffffefffffff |
|
VISUAL
dHash
|
4d0d060c0c0c140c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07003600000 |
|
VISUAL
cropResistant
|
4d0d060c0c0c140c,e02002a22303c3c2,e17876f3e1c1c4c2 |
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 23 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)