Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19653A874D1002D3FB3B75AE59D22F30A22F6E2C9EB42051435FCC6A827DAD72561E1E6 |
|
CONTENT
ssdeep
|
768:Bc+JMbjbEbS6dbnFbMb+JbVb3jbrbbbKeDbPX2bv6tbQblSozOSbtW+EEZbZlbeo:Bc+JPYxpmdCXTmdCXSPH7RopDbR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
884c7733559cdc36 |
|
VISUAL
aHash
|
0000191b1b1b0703 |
|
VISUAL
dHash
|
063733b333b31f37 |
|
VISUAL
wHash
|
03191b1f0f1f1f0f |
|
VISUAL
colorHash
|
00000038000 |
|
VISUAL
cropResistant
|
0f9f9f979f9fbfff,26d4dcd0952aa485,71e8cc8e969694f0,063733b333b31f37 |
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 89 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.