Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A67241306254897EA093C3D9E776333F22A9D295EA07434896EDC3285ECAC49EC376D4 |
|
CONTENT
ssdeep
|
384:IU1H6N4rQwiWbYDeTeqEj/SYWFC0vpyp0C:IUsjDOeqEj/SY+yp0C |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b8666793ccc99392 |
|
VISUAL
aHash
|
e783c3dbdfcfcfdf |
|
VISUAL
dHash
|
0e0f92b2b2999d9a |
|
VISUAL
wHash
|
c38181db9985c7cf |
|
VISUAL
colorHash
|
06001000180 |
|
VISUAL
cropResistant
|
0e0f92b2b2999d9a,1787079f9f2e2e1f,5c6a16a9e9695648,fdf5f5fdedfddded,0d2d6c3d71692317 |
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 30 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.