Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T188441AF8936853F496874BE4F9711A16335610EEFB914A88C3A48EE0FBE2DC9D435C61 |
|
CONTENT
ssdeep
|
6144:+Yn/mJoLXs4JwA8dNTPE9/zHMaAjH57gx4G1yqeHKaXlGiepOQRqIOkwuw7L7jD+:+Yn/mJoLXs4JwA8dNTPE9/zHMaAjH57k |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cee131ce8a29cf31 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
a8c4e8696969690c |
|
VISUAL
wHash
|
007e7e7f7fbc0400 |
|
VISUAL
colorHash
|
39001000c00 |
|
VISUAL
cropResistant
|
8d9983e6a6a686a6,a8c4e8696969690c |
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 632 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)