Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D112F926A700096E800B43D5E6929B55B33FC2DDEB6349ECF36C8A396785D38DB57780 |
|
CONTENT
ssdeep
|
192:avWoD9Zu7E5M6TgYSFYuz/8gpBb6Q7DQkK5QvTFUs+50Ljk/:6Wo/uYN+Yu75pBb6Q7DQkKyvTFUN50L2 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ccd87472727278d8 |
|
VISUAL
aHash
|
8038182018003c18 |
|
VISUAL
dHash
|
10f0b06870686060 |
|
VISUAL
wHash
|
d87e183c3c343c3c |
|
VISUAL
colorHash
|
38e00000000 |
|
VISUAL
cropResistant
|
a28ab04d4d0092a2,10f0b06870686060 |
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 217 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)