Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T164838279E2F7D3EBA45FBBE4A66133E0A05FD7ABE38217D8856843D507E0C50588B510 |
|
CONTENT
ssdeep
|
768:jjfPn3zvaBMszIjfPnEzGWukdPmeM9DHZzm1iKaXW:jjfPjvaNIjfPsGWd+eM9DHZzm1iKaXW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d333866c2c6fc343 |
|
VISUAL
aHash
|
006c6c4c4c40387e |
|
VISUAL
dHash
|
d8d8d999d0d8e8d4 |
|
VISUAL
wHash
|
406e6c4c5c6c7c7e |
|
VISUAL
colorHash
|
30001000180 |
|
VISUAL
cropResistant
|
ac6464322622c894,d8d8d999d0d8e8d4 |
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 968 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)