Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T158A35221A583AC7702B786D19077170960E2B308DA130996FBFD93FE47DEC69F92A194 |
|
CONTENT
ssdeep
|
1536:b4FsIx8pP7cN9AhA8vFl85O8By41Q8AXtb/AXv2h1RpfVazN6DJcOqQZFuFOd7cK:AExERaa4N7T |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ac08d26fd98e2d99 |
|
VISUAL
aHash
|
ff0700000000ffff |
|
VISUAL
dHash
|
22afa2aab3672f1e |
|
VISUAL
wHash
|
ff5f00010100ffff |
|
VISUAL
colorHash
|
06c00000000 |
|
VISUAL
cropResistant
|
22afa2aab3672f1e,1767352f0e2d2d0d,1f3b0f1f2f2e733f,6c694a4b4151252d |
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 78 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.