Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T168130038B002385761779AD0F091AF4D7182E73AC7448E68E3F922767FCBDE46864769 |
|
CONTENT
ssdeep
|
768:LmFlDischHg6lWnl4n7ZnAT2nOqncuhQzeAerEOTfK9wa220t2XYKM3MXH57a6Mt:LIlCg6+waT/tuWzCTiwqfWWH57a6M1sc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72366c888dd8876 |
|
VISUAL
aHash
|
e7e7e7efe7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d0c0c0c4c4d |
|
VISUAL
wHash
|
24242424e7e7e6e7 |
|
VISUAL
colorHash
|
070000401c0 |
|
VISUAL
cropResistant
|
4d4d4d0c0c0c4c4d,e9e10200402aaaf4,646464646418a8aa |
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)