Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CDA295B250E0203B02074ECDB0757FAE70D7819DCB57484192FE87D64BD7CE6E8AA51A |
|
CONTENT
ssdeep
|
384:goZGsIKhRLqYVtNgtK7lC1bsTNVqsBG0V4uSjNsV0NNegc+k1ahhZtO2htuumEak:lZGsIK/eQtNgtK7l6bsTNVq4V4njN+K7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
843d2d95953d85ad |
|
VISUAL
aHash
|
0200187e7e7e0018 |
|
VISUAL
dHash
|
b26170d4c4c4f0f0 |
|
VISUAL
wHash
|
1a10187e7e7e3c3c |
|
VISUAL
colorHash
|
30000e00000 |
|
VISUAL
cropResistant
|
b26170d4c4c4f0f0 |
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 232164 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.