Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19D831422B588707B427357496C70FB59F39B51998E2E0F056E70AB0E9DC5F86DC2328B |
|
CONTENT
ssdeep
|
1536:6DAgiiYP/0v70m33Deg62PhST6QIki9mzKZh:6EgiqJ33DeP2PhST6QIki9mEh |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3d966646632cc66 |
|
VISUAL
aHash
|
e7e7ffffffffe7e7 |
|
VISUAL
dHash
|
4d4d325810144d4d |
|
VISUAL
wHash
|
c3c3cbcb1b130303 |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
4d4d325810144d4d,c4cde2eae23739b3,60919262b0c68e31 |
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 5 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.
Pages with identical visual appearance (based on perceptual hash)