Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18EC2A878A60111A743F799C1F2617F1F72D6F30F80168656ABBC918A2FD3CB6B720166 |
|
CONTENT
ssdeep
|
192:vVR7PoLF80RFwLFOnIFIkEFDM4jEFTs+KRr720Pv9Xr4BbZE90al45OIx915xDzg:vOF8AF6FOIF8FDM+p |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3313163cecccccc |
|
VISUAL
aHash
|
c7c7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
1e1c040c0c0c040c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07600010000 |
|
VISUAL
cropResistant
|
1e1c040c0c0c040c |
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 12 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)