Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T142F263B35100153F4323A7C9F4217B5ED093830FCE9798A4A2AD87875BD7FE5896D82A |
|
CONTENT
ssdeep
|
768:+IKghtQIkS3s759jxANz+W4p8KCtb0wWOoAX+L7+3xfUand+0KLgJBEtBEdgYIpS:+IKghtQIkS3s759jxANz+W4p8KCtb0wT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
93566d936c929356 |
|
VISUAL
aHash
|
00000e0e0e0f0f03 |
|
VISUAL
dHash
|
4218dc5858585b03 |
|
VISUAL
wHash
|
c30e7e2e2e2f0f03 |
|
VISUAL
colorHash
|
31040007000 |
|
VISUAL
cropResistant
|
1252d23002472b0d,4218dc5858585b03,016928174d30b10d |
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 1021 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)