Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T167928932E10151B702B3A6C8E6B8BF1EB693F30FC816C504BEAD41951FD3DB5B5654A4 |
|
CONTENT
ssdeep
|
192:6elVRKna3AM8hTCIC8CgF7FFFIFOuFDVbTme7bVZc8x/tD:DWaQM0bxDF7FFFIFOuFDZD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b33366ccc9cccc89 |
|
VISUAL
aHash
|
e7c7e7e7efffffff |
|
VISUAL
dHash
|
4d4d4d4c48141044 |
|
VISUAL
wHash
|
c0c0c0c4ece4ece4 |
|
VISUAL
colorHash
|
07008000e00 |
|
VISUAL
cropResistant
|
4d4d4d4c48141044,0101050503010206 |
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 22 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)