Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T170B2A6A22090A42F156FC7C78F669B6873E660B7D6BA0241D3FD83CCCBD6D91DD06905 |
|
CONTENT
ssdeep
|
384:p1Ll0FRZ63QE/DFQr2J03RZ63hktsM3StmX2fGcTVP+W1w0wRZ6hQE/jFpr2f0oR:LCnZ63Jxp2BZ63hktsM3StmX2ueVP+Ys |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3c79c9c9c969a92 |
|
VISUAL
aHash
|
fe707c6000180018 |
|
VISUAL
dHash
|
f4c2c9c3d2303271 |
|
VISUAL
wHash
|
ff7a7c70003c383c |
|
VISUAL
colorHash
|
31600030000 |
|
VISUAL
cropResistant
|
f4c2c9c3d2303271 |
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 204 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)