Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13FA2DBF01315CAAE14D78778DB35A247635AD7A8F6060A4AA3EC875B3DC3CD1CC972A4 |
|
CONTENT
ssdeep
|
384:uLPynrHIZl73pZJqtyVM4uXoyBQgVVVV0nbAdm:uLPynjIZlzLJqtyVMJXouQgVVVV00dm |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a6db2e532cd9261 |
|
VISUAL
aHash
|
421818183c3c3c3c |
|
VISUAL
dHash
|
b27132326969616d |
|
VISUAL
wHash
|
ff1818183c3c3c3f |
|
VISUAL
colorHash
|
30007000000 |
|
VISUAL
cropResistant
|
b27132326969616d |
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 241 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)