Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T153443AF4835853F096874BE4F9711A56339610EEFB914B88C3A48AE0FBE2DD9D439C61 |
|
CONTENT
ssdeep
|
3072:euDITa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1D6:j77jDw/47g7/ta |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8e3131ceca6fce30 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
aadc686969696904 |
|
VISUAL
wHash
|
007e3e7f7fbd0400 |
|
VISUAL
colorHash
|
39001000c00 |
|
VISUAL
cropResistant
|
8d9983e6a6a686a6,aadc686969696904 |
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 594 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)