Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12CF253B2D494653B01D7D2C4B72DBF4AE3C381DBDD16558167F883488FCAE83D862A29 |
|
CONTENT
ssdeep
|
192:Deqcy0tb7E9MpkAHsyYrWQnIo+wqHcoTqyHOPFmHITTa25JI+YoqHcoTqyls:Da7t/IMpkAH/YquIo+0mAkIM+H3 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e4649b9b933239cc |
|
VISUAL
aHash
|
c3c3c3c3ffffffef |
|
VISUAL
dHash
|
06a68686181a1e1a |
|
VISUAL
wHash
|
83c3c3c3c3cbc3c3 |
|
VISUAL
colorHash
|
06000000006 |
|
VISUAL
cropResistant
|
06a68686181a1e1a,cec6a280e2d29626 |
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)