Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EDA2E82112582B7E212387E8F7A5F3745259D18FD32AC269E97D03702683DD8E833ED8 |
|
CONTENT
ssdeep
|
384:uvboRX9PY+0tcFoJOrctCvQsOyvuvUvHvrrvby2NjaNcFK:+oRX9PYEFoJOgtCoryvuvUvHvvvbykaR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf136dc66949c0e4 |
|
VISUAL
aHash
|
00040000ffffffc3 |
|
VISUAL
dHash
|
1b5c5c1b1f042b2b |
|
VISUAL
wHash
|
00060600ffffffc3 |
|
VISUAL
colorHash
|
0b000000006 |
|
VISUAL
cropResistant
|
a280829a9a8280a2,1a642727c82b232b,981a195c5c1c181a,4d3228aaaaaae869 |
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 22 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.