Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11083963122041A3EE657CAF4F2B1773961AEC349DA2FD45CF5B802B227C2D58DD27698 |
|
CONTENT
ssdeep
|
768:XaAOui6E+Ngi0dpYT7rjXoCYuYg+Y6YIpQF3bvfVjYLYeYGYYYRZ3zQO/XUGB/Ya:N7rboZpQPFR1j/KdZBI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce3164d3c66970da |
|
VISUAL
aHash
|
000000083c7c3830 |
|
VISUAL
dHash
|
c4ecfcf069f8a0a0 |
|
VISUAL
wHash
|
000f0f1e7c7cfc78 |
|
VISUAL
colorHash
|
30000000180 |
|
VISUAL
cropResistant
|
2929d3b36a4ad44c,192ce9dad22676e5,c4ecfcf069f8a0a0 |
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 253 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.