Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18BA3FE38B1067C16647795C0F0946F997282EB3AC3448E58E3F527A62FCBDF468A5378 |
|
CONTENT
ssdeep
|
1536:LVeMc6MZhK7jFB0oz+mgDqRdCXSPNKuecY12Q52a6/IMvImJjPwtahIzHz+Qow23:/MPMBAXvM/3n |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72266c888dd8877 |
|
VISUAL
aHash
|
e7e7e7ffe7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d0c0c0c4c4d |
|
VISUAL
wHash
|
04042424e7e7e6e7 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
4d4d4d0c0c0c4c4d,e9b01200002aaaf4,64a4a4a4e498a8aa |
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 524 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)