Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18B1398212240292E671707A8B9E4F77892BDE79DC167895DF3BC01B317C6D6D8B232D0 |
|
CONTENT
ssdeep
|
768:ktL7EL/pEsCgE1oYuah6iZZYZFgykyEymy7yaySywyLYAYA7zRlrJMKXyqS765ut:g5+23/7O/z/m7FRJMqS765uIAGuhn |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e66989ba9d969162 |
|
VISUAL
aHash
|
fff1f08484e4f4ff |
|
VISUAL
dHash
|
31250d2d2dad2d2d |
|
VISUAL
wHash
|
fdf0f00490d4f4f4 |
|
VISUAL
colorHash
|
06010000c00 |
|
VISUAL
cropResistant
|
31250d2d2dad2d2d,c0dcd8c0c4d4d0d8 |
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 12 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)