Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11CC251F31100E99E1622C7CDB823BBADD05B751DC9E5DCA9F3590B631682FE086D9836 |
|
CONTENT
ssdeep
|
768:zLPWWVxHk/3ynI0Lpd4ZygXleoAa/fxk0jLf3:zLPjVxHk/3ynI0Lpd4ZygXlB/5k0j73 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc8933cc6633d9cc |
|
VISUAL
aHash
|
0018181818180000 |
|
VISUAL
dHash
|
2432b2b2b2b20810 |
|
VISUAL
wHash
|
101838383c3cc0c0 |
|
VISUAL
colorHash
|
38000030000 |
|
VISUAL
cropResistant
|
8c2b335555332b8e,a61616464b5b1484,0901494901314e4d,aa2aaa90d4a23d84,2432b2b2b2b20810 |
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 71 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)