Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11BB49FF1A62C11BD009787CAEB717958231EE1BBF595C8906A5D4AB41FE3CA4FD0BC90 |
|
CONTENT
ssdeep
|
12288:oHI8q90M37heoHrcwVOBhBxf1Whbv1ifUQjQQN:iI8q1/HrtV8hBxN20UQjQQN |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c50225fbaa2d5daa |
|
VISUAL
aHash
|
00000000ffffffff |
|
VISUAL
dHash
|
d7ccc4d200223233 |
|
VISUAL
wHash
|
00000000ffffffff |
|
VISUAL
colorHash
|
1e0000000c1 |
|
VISUAL
cropResistant
|
0221693232333333,cb04d4c4ccc492cc |
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 144 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.