Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11322E128396445BA03372B91B4E1EE5978D2F70EC463D5B0C1FF63E956D4ED18C94836 |
|
CONTENT
ssdeep
|
96:82p118+iVK2HlV7l8fiXRkYJV08zgAtuixt1K8cfpJy3eiHSd5JmuoiDOyimIUm1:Pp1WVzj7lpvK8UytsnogOSc/ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8eaaabaaaaaaaa2a |
|
VISUAL
aHash
|
ff3c30300000003c |
|
VISUAL
dHash
|
6168616000000068 |
|
VISUAL
wHash
|
ff3f3c3c2424243c |
|
VISUAL
colorHash
|
38000008c00 |
|
VISUAL
cropResistant
|
6168616000000068 |
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 1087 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.