Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A8429472A045213702335ADFB171BB76B2C3825DCF1F4D01A6BC53DE4BD2E66E91928A |
|
CONTENT
ssdeep
|
192:8IxOAW0XayClJljKM0ft3yEzT/+SdcMcMssMfHKAFh:PXXWKM6VyEzTmSGMcMlMfHKAFh |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e8b5c75a846913ad |
|
VISUAL
aHash
|
ffc3c3d3d3cdc1ff |
|
VISUAL
dHash
|
568e9aa2a3191348 |
|
VISUAL
wHash
|
ff020043d1cdc1ff |
|
VISUAL
colorHash
|
07001600010 |
|
VISUAL
cropResistant
|
404d5d86969e9e8e,8db3ee9820c08402,9aa3a6191913134c,56520aaa6c646665,a280a28e8ca280a2,868e9aaaa6191913 |
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 190 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)