Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T143D209705AA1E63B02E3C2D467366B9B7BC18348CA63174653F9C34E8FD7E86CE56241 |
|
CONTENT
ssdeep
|
768:CPLtMCFb5tvvidZu07J+H548KNfH2rRvvuGb/qaISo:2MCFb5tveZu01gRvmGb/qaISo |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c31c3cc73c3c38e3 |
|
VISUAL
aHash
|
0070600060706060 |
|
VISUAL
dHash
|
26c0c0c0c0c0c0c0 |
|
VISUAL
wHash
|
ff7860787870f0e0 |
|
VISUAL
colorHash
|
38000000038 |
|
VISUAL
cropResistant
|
26c0c0c0c0c0c0c0 |
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 144464 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)