Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T197A2647025315ABF549B93F0F661AF6961D9878CDA97D66C62ECC2A91FC3C70CE8C210 |
|
CONTENT
ssdeep
|
192:y9AgPx9qfxfRUfaPVVQhEIjpqYPXd8u8m8/fh7c8jk3MLj0V8Z8Ch3/krDy4Pa2g:y9AOqJz5Idd5FaRHgVyKrDyWM |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b83acdc93832a6c7 |
|
VISUAL
aHash
|
fb9b8787cfffffff |
|
VISUAL
dHash
|
333b2d3d3c500832 |
|
VISUAL
wHash
|
8100070787874fff |
|
VISUAL
colorHash
|
07219000000 |
|
VISUAL
cropResistant
|
333b2d3d3c500832,f296969299f06464,c8e8f2909244c4c4 |
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.