Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B75409F8835813F1968B8BD4F9715A0A339611AEEB92475883F48AD0FFE2EC5D435C61 |
|
CONTENT
ssdeep
|
3072:MgDuSJTa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1D1:xvI7jDw/47g7/tV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce6131ce8e2dcf30 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
aadce86969697904 |
|
VISUAL
wHash
|
007e7e7f7fbc0400 |
|
VISUAL
colorHash
|
39001000c00 |
|
VISUAL
cropResistant
|
8e8999e686a68799,aadce86969697904 |
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 613 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)