Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T145132BEAA6D024D5B00783E1EA25F495B50BB0FFDFB6DB54EBD84905248787C8C85BC2 |
|
CONTENT
ssdeep
|
768:j7F5QckDb8sVL3Mru9KTYNKkNeJ2sSvmHhn/LxQnuLmAXVtFe:5eLVKxJxU4XVtFe |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
81ff04fe3330dc8a |
|
VISUAL
aHash
|
bdffffc7cf7f3f3e |
|
VISUAL
dHash
|
2100109c9c80d0c4 |
|
VISUAL
wHash
|
98fece46463e3e02 |
|
VISUAL
colorHash
|
07007400000 |
|
VISUAL
cropResistant
|
2100109c9c80d0c4 |
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 3462 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)