Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A8138330A006ED3B4083D6E4E6366F5B73E09285CE131656A2F4CB1D9FDFC91CE5A265 |
|
CONTENT
ssdeep
|
768:Vos44XS44s44GG448yrkYx1sKwHRYLRiRR4KiT+YQoPqx5RJsnfd4YuaX:Ws44XS44s44GG448yxH6HRYLRiRR4KiT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d32dbcb8d3a148b8 |
|
VISUAL
aHash
|
ff0000000000ffff |
|
VISUAL
dHash
|
6264c6c9c9d92714 |
|
VISUAL
wHash
|
ff7600600400ffff |
|
VISUAL
colorHash
|
03000000e00 |
|
VISUAL
cropResistant
|
80206a7b7b6084e4,0000000000034414,c43bc6c8c9e9d989 |
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 23 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.
Pages with identical visual appearance (based on perceptual hash)