Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EE2418A0639151ECE6638B94E070792220BB73AAF463C35CD9DE1161FED6CF598398D3 |
|
CONTENT
ssdeep
|
1536:LU7tZkVzN1PLnkXwdU5HJNKDkopwZmfelyu+z3AaUMP2RxvF1lGb8clcVHJzWNUC:LUKAg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b1cc89dd64336173 |
|
VISUAL
aHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
dHash
|
96869696969e8e9e |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
06007000000 |
|
VISUAL
cropResistant
|
0202020202020202,a0a0a1a0a0a1a0a0,ece2e5919b9b12da,e096aa23231e162e |
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 87 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.