Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D6621134919209BF62974DF6B6A1BF3B90EF8A0EDB57DBC892EC02B533D6D049201750 |
|
CONTENT
ssdeep
|
384:wRmuYrYse0hFfkmw5jeELcnarvFKsLYjYG:WpYrYjmw5qELcnuFKsLYjYG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f837414b07b435d6 |
|
VISUAL
aHash
|
0000c7939999fdff |
|
VISUAL
dHash
|
10112e2b2b2b33b3 |
|
VISUAL
wHash
|
000097839999ffff |
|
VISUAL
colorHash
|
07000038000 |
|
VISUAL
cropResistant
|
0b262b2b2b33b3b3,8008000c32121011,e3eb8bd9bbf9f347,6d4d595599b832b2,b9f8707872787870,7151157d59595c57,51717865545494b1 |
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 8 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.