Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10A918526A65CCD2F6233C6D5F6D27208949B915AE02C9C14E1BF03ED42D6EC1DC7B159 |
|
CONTENT
ssdeep
|
96:sWKMP78zKK1Gd7vB3DvJxK557rEATbBENPt8Yts2:sWKu78zKK1G1FKerL |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333174bf0b44b0b |
|
VISUAL
aHash
|
0f0f0f0f0f0f0f0f |
|
VISUAL
dHash
|
19d85b9a9bfbdcdb |
|
VISUAL
wHash
|
0f0f0f0f0f0f0f0f |
|
VISUAL
colorHash
|
03000000e00 |
|
VISUAL
cropResistant
|
90819ebd96968186,0a4acb33a5ca6a2b,6d6973a697557551,9fdfbf81e0befbfb |
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 13 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.