Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13D442AF4935853F096874BE4F9711A46336A10EEFB914B88C3A48AE0FBE2DD9D435C61 |
|
CONTENT
ssdeep
|
3072:egDrTa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1DX:Ra7jDw/47g7/t3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cee131ce8a2dcf30 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
aacce86969696904 |
|
VISUAL
wHash
|
007e7e7f7f7c0400 |
|
VISUAL
colorHash
|
39001000c00 |
|
VISUAL
cropResistant
|
8d9983e6a6a686a6,aacce86969696904 |
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 600 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)