Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T195A36C7036546A771AF783E3B0CB6A01A16D872BD40F4D607244ED6A33DDCE298A3BD5 |
|
CONTENT
ssdeep
|
3072:ZdDGRUhtQZZZpZxZvZlZUZPZ5OGJ1UANVz5z4I7:+DTf1na53VzN42 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
caa2b4f6e6a0a2ea |
|
VISUAL
aHash
|
ff18383838183838 |
|
VISUAL
dHash
|
e1f1f1f131313030 |
|
VISUAL
wHash
|
ff3c383838383c3c |
|
VISUAL
colorHash
|
02400018000 |
|
VISUAL
cropResistant
|
e1f1f1f131313030 |
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 35 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.