Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A3239031C051146F55279DE7B670B79E61E7870CD932986093BC4FADEBEAED08B22483 |
|
CONTENT
ssdeep
|
384:lpJXO3HTDDUa1Ki4C/HghVlI5VHn/RWv/6l5I/hDxNxfv9UA/BZZxWlFMUxknD+p:lzCndg6y/hDjtv2A/BZZxWsUxknDa |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc663399339ccc66 |
|
VISUAL
aHash
|
0000181818181800 |
|
VISUAL
dHash
|
4c48b2b2b2b2b24c |
|
VISUAL
wHash
|
0420bc3c3fbffe00 |
|
VISUAL
colorHash
|
07201000400 |
|
VISUAL
cropResistant
|
b1898b3a1ccca6aa,4c48b2b2b2b2b24c |
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 74 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)