Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11443F825608E156B01B794C7E521FF3960C6F30BEB7E46486EA84B991FCBDBCF50A060 |
|
CONTENT
ssdeep
|
384:vjSXUQu4VpMqAYH7h8XkRqV3qYGUixaCZ3:vjEMqAYH7ohds |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333398cccccccc |
|
VISUAL
aHash
|
e7c7e7ffe7efefff |
|
VISUAL
dHash
|
4d4d4d040c0c0c0c |
|
VISUAL
wHash
|
03030327c3c3c3c3 |
|
VISUAL
colorHash
|
070010000c0 |
|
VISUAL
cropResistant
|
4d4d4d040c0c0c0c,39a4ae9efd36ee59 |
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 69 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)