Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17F926130B1F19235917FB2DFF2617B25D0A7E34B82920BF14AF486640BD29E6B91F518 |
|
CONTENT
ssdeep
|
384:P+8xFTPhlSxI370AxlYjPoNM6oU5mLy3LJtZVrbYA:P5x5PhlSS370AxOzUM6PoSLJtZV4A |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b86d65617d306565 |
|
VISUAL
aHash
|
c3ffc7cfdfcfcfdf |
|
VISUAL
dHash
|
96303ebc301c3c30 |
|
VISUAL
wHash
|
81c38387cf87878f |
|
VISUAL
colorHash
|
070000005c0 |
|
VISUAL
cropResistant
|
96303ebc301c3c30,00c121212120c100 |
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 6 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)