Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1163392369904213B063712CDF02A7B5EF0E3C34ECA4354A4F3AD57DA0BDBD94E56A929 |
|
CONTENT
ssdeep
|
1536:gnGzO1dzEhtDkqHBqtLj35bd6ttumGVS8DeqY17GgBJYmxzDkBHTcbmIulh341CG:gnj1W9mhkfNMMT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a356ad2d542db952 |
|
VISUAL
aHash
|
01300c04040b0327 |
|
VISUAL
dHash
|
42c8c8ccd8fbcfcf |
|
VISUAL
wHash
|
03782c7c1e1f076f |
|
VISUAL
colorHash
|
31000006000 |
|
VISUAL
cropResistant
|
804b726971710c14,42c8c8ccd8fbcfcf,016928174d30b10d |
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 1725 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)