Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14403922622041E3DA997C7E4F3E8B378A12AD2D9C217554CF2AD01B527D2DA4E82F7D4 |
|
CONTENT
ssdeep
|
768:pJmz7YpY0CHSuq6Y6JNndqKZyA6G4RCPI1Oz5Z13s9h7uhENmiP9+bN7DxnFhbXW:pJmOjAyA69ggw9z8XyxB7DxTW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b21acec6cfd83232 |
|
VISUAL
aHash
|
bdc7c3cfe7c7dbe3 |
|
VISUAL
dHash
|
611e9e120e0e1616 |
|
VISUAL
wHash
|
85c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07001000380 |
|
VISUAL
cropResistant
|
611e9e120e0e1616 |
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.