Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T119733321E3329174A39F4A7EF0A0AF1EB3BDB3039710B8A5592718D51C4F569E1D7E22 |
|
CONTENT
ssdeep
|
1536:+nTLAXQ6monTLAXQ6mWZTLAXQ6M7On9GD:OLAXQ6XLAXQ61LAXQ6COn9i |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc3333666699cc |
|
VISUAL
aHash
|
0018181818180000 |
|
VISUAL
dHash
|
0010323032320800 |
|
VISUAL
wHash
|
30383c3c1c1c1c0c |
|
VISUAL
colorHash
|
38007000000 |
|
VISUAL
cropResistant
|
0010323032320800 |
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 42422 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.