Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BC34E8F0600157BB271749D0B0B1AE59B24EB34CCA1799C8B3BC59B37ECDCD60C56A9A |
|
CONTENT
ssdeep
|
1536:LnrLzWDuUhhhhhh8FAsIhw2cX+oc7I6rRzQ9:L/PO8iBFk9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
eec913970a49eb49 |
|
VISUAL
aHash
|
fffff9f9ffff0000 |
|
VISUAL
dHash
|
63337323234ca595 |
|
VISUAL
wHash
|
b99ff1f199f70000 |
|
VISUAL
colorHash
|
0f003008200 |
|
VISUAL
cropResistant
|
5378337323236f0d,92609a9696966896,02c00b1b2b2bd402,c8c8a09696aa8ae0,010111ceceae0181,88b5950095950094 |
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 4263 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.