Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19F925822F200517702B39AC8E6B8BF6EB6D3F30FC417C6046AAD51952FD3DB5B9214A5 |
|
CONTENT
ssdeep
|
192:66VREoU1bQ1mm9XSjV8+DM8jvCYCsChF7FFFIFOuFDVbTmWDZOzJ0Oc/tD:ZVoM6fhKF7FFFIFOuFDy2D |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b33366cc89cccc99 |
|
VISUAL
aHash
|
e7c7e7e7efffffff |
|
VISUAL
dHash
|
4d4d4d4c48141044 |
|
VISUAL
wHash
|
00000004efe7efe7 |
|
VISUAL
colorHash
|
07008000e00 |
|
VISUAL
cropResistant
|
4d4d4d4c48141044,0101010501010206 |
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)