Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T114C21E2151966F37C083C3E5A375273A23648A4DCFE616284EEF836AC7DBD84EF22155 |
|
CONTENT
ssdeep
|
384:6p/9CFpwZ0rINUor9N/wka5beNdOkCl9kje3kDkgRkbrkqk6kUkw2qXI+3KDlXIi:i/9CFAdrKevb7xh+6ZXIin |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ac38c3cfcac9682e |
|
VISUAL
aHash
|
f9c383d393f3ffe7 |
|
VISUAL
dHash
|
231f37372727060f |
|
VISUAL
wHash
|
d983819191c1ffc7 |
|
VISUAL
colorHash
|
07001000180 |
|
VISUAL
cropResistant
|
231f37372727060f |
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 178855 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.