Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18B334031E944E82301EB95C8E272172A62E64345C6630789FAF9C7FA5BDFC6DDA37101 |
|
CONTENT
ssdeep
|
1536:osIxFdWi2S/PT60HQZYa3QZTgPQZ48wQZKeL/N1xr/NmO7/NpcM/NmvHLlxV3LlK:ol3/r60HQZYa3QZTgPQZ48wQZKeL/N1P |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
de34a86b99463617 |
|
VISUAL
aHash
|
ffff00000000f0ff |
|
VISUAL
dHash
|
bb266c7450492930 |
|
VISUAL
wHash
|
ffff00040000fdff |
|
VISUAL
colorHash
|
0be00000040 |
|
VISUAL
cropResistant
|
8080a08080808000,1000303033802b33,290048343040249b,0000000000000000,266c6c70514c0929 |
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 87 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.