Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T161B3ED34A9A2685B68BBD5C0F4717F04249BD736C20C4FB8637A26A57BCACF45833764 |
|
CONTENT
ssdeep
|
1536:z5vGgrfgvAgTygfMZGJa5O6wwsGoe1GZ2HIW+OUJspEfxz/TzhBeC30:z5vzO6wwsRzS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b38c66999933cc99 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d4d4d4d4d4d |
|
VISUAL
wHash
|
e0e0e0e027270707 |
|
VISUAL
colorHash
|
06e00008000 |
|
VISUAL
cropResistant
|
0000000000000000,0000000000000000,8844389e860e3086,6145ec7878f02b19 |
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 915 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.