Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E4413E3140222D6B111BAEC87AD0EB5A38C3C30ECA77191853FC96AE1BD6C81EF1146A |
|
CONTENT
ssdeep
|
24:hRxO/Cl+gQmmpJnuhGZphWm8MxWg5bcNu9uENBCAYNaP6AGHb0e2hsfbDNPWmS9x:TxVp5mpJugZpcMxGAxjcqG70KTDNI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e60f4b96346993c3 |
|
VISUAL
aHash
|
f0f0f0f0f6f0f0f0 |
|
VISUAL
dHash
|
2724642424042425 |
|
VISUAL
wHash
|
f0f0f0f0f0f0f0f0 |
|
VISUAL
colorHash
|
06038000000 |
|
VISUAL
cropResistant
|
ca0c120c0c000000,f086aaae92aa8245,122e36b0f8cc9898,0c70697971717004 |
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 684 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.