Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19A1231B4A1A64F7F60A387B1B3A67B2B61D8C34ED547828EC3ED83A917C6C50ED15300 |
|
CONTENT
ssdeep
|
96:VIqUIYg4z8zPBK2sP2eIiS3Nu6P6UyT6vo4WzIjEb+UlK3eiKP2WOiPik0idAdsr:VBU2jYKnkvpKU8On2WOeAtds592fF2t |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a666666633cc9999 |
|
VISUAL
aHash
|
e7e7ffe7ffffe7e7 |
|
VISUAL
dHash
|
4d4d080c180c0c0c |
|
VISUAL
wHash
|
24242424e3e3e7e7 |
|
VISUAL
colorHash
|
07000000007 |
|
VISUAL
cropResistant
|
4d4d080c180c0c0c,806c939296916880 |
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 78 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.