Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13221236050644D7F9106959463E9D71B3556CF52CFA71600CBFCD3FD5AE5E80CD28191 |
|
CONTENT
ssdeep
|
24:hR/T8MLiNjnBeTuXZtEwwN9uSG0/c3HW/0/5Nv:TwKkY83IH2Ymb |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc666666669999 |
|
VISUAL
aHash
|
0018181800000000 |
|
VISUAL
dHash
|
2cb2b2320c300000 |
|
VISUAL
wHash
|
ffffffff00000000 |
|
VISUAL
colorHash
|
38000000e00 |
|
VISUAL
cropResistant
|
c2d8bae2c0697113,2cb2b2320c300000 |
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 8 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.