Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1609372716183AC374163C2D0E27A6F1DA1C5A30DCA120D56F7FD876A9FDAD64FC2A1A0 |
|
CONTENT
ssdeep
|
1536:ASnB44xJjpIDmeBUFnTMf/RRByn4GvlR4aEbZcVXpfnizN1COqXZQZ8h/m1pIDm4:ZJsvTsx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed3a9666d4926839 |
|
VISUAL
aHash
|
fffb899991f1fffe |
|
VISUAL
dHash
|
2c323333332302b6 |
|
VISUAL
wHash
|
06bb819191f1f87e |
|
VISUAL
colorHash
|
07010000480 |
|
VISUAL
cropResistant
|
2c323333332302b6 |
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 119 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.