Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19B332F712243582BE5A785D1F7413F5AE1CAE31AC6134C85FBE9C2779F8BC24BC29624 |
|
CONTENT
ssdeep
|
768:VgKqww3/4CE7+bwCkV2euOKKJJDFhrUrJrGrbrk+bgpWAbb8n/y9zjoZju+PPkAK:cPZbuV4+QNqXoNpUl6yLw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bb44bf4439e413a5 |
|
VISUAL
aHash
|
000000400000ff8f |
|
VISUAL
dHash
|
921ece8390e31b18 |
|
VISUAL
wHash
|
00c0e0e0783fffaf |
|
VISUAL
colorHash
|
02070000200 |
|
VISUAL
cropResistant
|
b2821216228292ce,9616001a1a3a1858,921a1c8a8290c6f3,929230381a326248 |
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 112 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.