Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CC42E1315088B5B71183A2D5A7366B8AF7D2C246CA735B02A3F9C38D6FE6D43CD23615 |
|
CONTENT
ssdeep
|
192:EdfhvzESJH8BncdqW4r0bPofHJodJSLqiNnC9/7DuRVTo:YZ7EncyOPUpucmis9/7DkTo |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
922dad328d6dc22f |
|
VISUAL
aHash
|
030474440c6c007e |
|
VISUAL
dHash
|
3beccccded8d2ddc |
|
VISUAL
wHash
|
831e7e647c6c047e |
|
VISUAL
colorHash
|
38200030000 |
|
VISUAL
cropResistant
|
f0f467785a1bd8f0,8080809818485858,8080809c0c5c0c0c,a0aca28d8d1d1d0d,3beccccded8d2ddc |
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 949 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.