Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EA7275B48145B177028752C0A737BBADE382D2C4C7120B0A95F9C76E5F9AE49DC3B5A8 |
|
CONTENT
ssdeep
|
384:RDxe3ZGNHHk+5aeKz0d08vJOvqBUSD2PpuFPvcD1:p2Zd1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b81c47473a334d67 |
|
VISUAL
aHash
|
00ffcb8f8fffefff |
|
VISUAL
dHash
|
99c7163b3a334c0c |
|
VISUAL
wHash
|
0071838383f3e7ef |
|
VISUAL
colorHash
|
0e200000003 |
|
VISUAL
cropResistant
|
c1163b3a3b834c0c,00001e9e40428080,d8d8d8d8d8e8e6cc |
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 979 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)