Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11CE36794826213E6106746D1B7E16B68E0BCD748E6278C4DE3AC826B17CDCA43787FD7 |
|
CONTENT
ssdeep
|
1536:4X8L83oB3WHe/123/w38F3mX3j03iT3H43FG3A53MV3Of3WH3123q7eJLWFG3EN8:EdVFdRuRdRLRSfqY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b74ab8b5c8a7a069 |
|
VISUAL
aHash
|
83000070640f0ff0 |
|
VISUAL
dHash
|
4b4d4dc5cc6c6e81 |
|
VISUAL
wHash
|
fb040470e70f0ffc |
|
VISUAL
colorHash
|
320c1002000 |
|
VISUAL
cropResistant
|
0010070e99b3ead0,f4f49233a88a88dc,4b4d4dc5cc6c6e81 |
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 94975 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.
| ID | Portugués | Inglés | Trigger |
|---|---|---|---|