Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FDB20175D0449ABB058727E0D7309B087283E38BCF230686D6F68369EF9AE59CC176D5 |
|
CONTENT
ssdeep
|
384:1y16JntFmuNlN74PtuGNC2Wb0MD5EzNMADQ319Yu3mO:1y16JtFh3OQl9YuWO |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8e4b336dc429f346 |
|
VISUAL
aHash
|
003c3c7cbe83013c |
|
VISUAL
dHash
|
d161e9e5241e8bec |
|
VISUAL
wHash
|
003c3cffbfc3013c |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
9020002c3c2c4820,ecece4e4e4e4e4e4,e4b271b2b0b1b1ac,e6c8eee6e4e4c4e4,802020402c3c3c2c,d161e9e5241e8bec |
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 57 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.