Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T186427A70C2A6256B017BB1C7A8759BE938E2824FC5170218EABC47AC5FDFDA07D5640A |
|
CONTENT
ssdeep
|
384:G4OpeF4TocCjFLiSj1+PjoEaJnDs5bzrYO2vqYoygOdXXVtMLafosabc3Vn3qU8P:G4OpeF4TocCjFLiSj1+PjoEaJnDs5bzJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9d59591dcea4e017 |
|
VISUAL
aHash
|
000000ffffffffff |
|
VISUAL
dHash
|
7070d06d6d926c61 |
|
VISUAL
wHash
|
000000f717ff1fff |
|
VISUAL
colorHash
|
0f0010001c0 |
|
VISUAL
cropResistant
|
3438bcb8ccc47030,92496d72806264d1,f0f070327279f0d0 |
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 82 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.