Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12172F96EF31513704A4203DEFB6B22FDF613409992126B9CDB78421DB3A5AEDC425DC5 |
|
CONTENT
ssdeep
|
384:QgoCnxNIFxPKuP6mtx9AW2z5ismMpBZ7eg/B:To0jwx6mtd21Tm4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a55aa55a8 |
|
VISUAL
aHash
|
0081e7e7e7e7e7e6 |
|
VISUAL
dHash
|
4b0b0f8c4c0f0f8e |
|
VISUAL
wHash
|
0081c7e7e781e7e6 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
4b0b0f8c4c0f0f8e |
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 485 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)