Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T101C15332601D613780274BCDBA767659A5FF916CE6230C04E7FC4BE56BC8C8ADC32999 |
|
CONTENT
ssdeep
|
96:TwSI13Z7fHr1EuTosevD/nz1oYMiqyvY4O9r8DHm5/Q3azdy:ovT3mCRyv0CGxI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
95568707ce1b5a47 |
|
VISUAL
aHash
|
00020080ff6f2fff |
|
VISUAL
dHash
|
d4aa9831a6da56d5 |
|
VISUAL
wHash
|
00000088ffff3fff |
|
VISUAL
colorHash
|
03000038000 |
|
VISUAL
cropResistant
|
808082c0c28000c2,acaa1931ae5a5695,0040d4c0c0d40003,6f2bcf6733991131,23f3e7e5a62c2931 |
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 29 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)