Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EC51FE3090008D3F126B6DD8F571272EA0E7C34EC6130888B7F853DAA7DEDE9C666246 |
|
CONTENT
ssdeep
|
48:HipV8345IZUve2W2zOU3T5q2aNNoYz0UREehEZ:Cpm345IaTWWOMTUxNREehEZ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9c33999999e66632 |
|
VISUAL
aHash
|
1818181818181818 |
|
VISUAL
dHash
|
b2b230b2b2b2b2b2 |
|
VISUAL
wHash
|
3c3c3c3c3c3c3c3c |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
c63063215c4d9001,0707060607070707,9090501090909090 |
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 1764 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.