Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A9333CE87442F1226A7342E350EF6907737A470BE40E4860E368EACA77F48197467FD9 |
|
CONTENT
ssdeep
|
768:mMeZq6FTY5MP+y4cnvMlI9Ufqz/dRHbyMBWk2l5lYQi/y:V+ocnIEdRXQZ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8c626e9c33337399 |
|
VISUAL
aHash
|
1818701e1f1f1f1a |
|
VISUAL
dHash
|
b2b2e4b2b2b2b232 |
|
VISUAL
wHash
|
1018781f1f1f1f1f |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
b2b2e4b2b2b2b232 |
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 129 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)