Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T113421AF5722412A1DE0343DAF96623BEE103826EDD6256C8D7A98718B2C5DFDCC51EC2 |
|
CONTENT
ssdeep
|
192:QokoBO5tAnpjr48v0eJfqku9cuGRmKbMpBXp7sfgg8gk:QTokUrhNsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b992c6c6c69a939a |
|
VISUAL
aHash
|
ffc3c3c3c3c3c3c3 |
|
VISUAL
dHash
|
0e1f1b1b07171716 |
|
VISUAL
wHash
|
ffc3c1c183838383 |
|
VISUAL
colorHash
|
1e4002000c0 |
|
VISUAL
cropResistant
|
0e1f1b1b07171716,fefdf5e1f1f3e6e0,34303038bcbc9819,19d8d8c991c96161 |
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 490 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.