Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C5C23F7551726E3F018381D2EA306F5AA3C2D34BDBA38B9693F8D3598FD6C91DC16224 |
|
CONTENT
ssdeep
|
384:/b3044O4U6iqykatOH25fXVu8B94zRXwDOs4rUytq4k:/b3044Oc5ycKfg8neRgDOzrUytqr |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
931bed6c6cb21236 |
|
VISUAL
aHash
|
00000c0c00ffffff |
|
VISUAL
dHash
|
23c9c9d922950ccc |
|
VISUAL
wHash
|
002c2c0c00ffffff |
|
VISUAL
colorHash
|
020000001c0 |
|
VISUAL
cropResistant
|
258888cc8ae8a4a5,0469970c4c0cb2d4,2bd6c9c9d9f926c8 |
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 135 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.