Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T148A101E1C461663B012387E4F8B717EAF4EB911ED887481063EC97EE5BD6C80EA76C11 |
|
CONTENT
ssdeep
|
96:TEJIW9V+r8HFbbE+lviQs3noN21WAnvrhHswntB1JsErS1sA40m1HE:HW9V+rUNIrXb9bE |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf3f5f51c24051c4 |
|
VISUAL
aHash
|
0081818fffdfffff |
|
VISUAL
dHash
|
79713f3bdc1292ea |
|
VISUAL
wHash
|
00000181ff8fffff |
|
VISUAL
colorHash
|
06006000040 |
|
VISUAL
cropResistant
|
0000000000000000,71373b7d961292ca,84397b7171373f3b |
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 36 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.