Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D8837DE97980B0D4A51383E290BF7416733F603F6D2DCA20E394ED8974A642D949BFC6 |
|
CONTENT
ssdeep
|
768:RTfpUCMr1XVVL3Mru9KTY+KkNeJ2sSvmHhn/L3QnuLmAXVtFPWv+p4yTMHeIv6Rc:ojLVKmJxm4XVtF+ryTDqQQZ5 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
81ff04ee3330ccce |
|
VISUAL
aHash
|
fdffcfc7cf7f3f3e |
|
VISUAL
dHash
|
1100189e9c80d0c4 |
|
VISUAL
wHash
|
b8fece46463e1e02 |
|
VISUAL
colorHash
|
07007400000 |
|
VISUAL
cropResistant
|
1100189c9c80d0c4 |
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 1874 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)