Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D6E3AEB9D0461237469BE4C6F8E29B5F6AE3930ED9431719A3F88791BFC2DD1E912C10 |
|
CONTENT
ssdeep
|
768:e/JBXGPSmMtKg25/iU6xBtM3MeS+MQ2vXZj61Esaq8QBgJ88I9SGfWa86YLmSw1V:e/ACD3ysGtWESQ9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cee131ce0a2dcf31 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
a8d4686969696904 |
|
VISUAL
wHash
|
007e7e7f7f7c0400 |
|
VISUAL
colorHash
|
39001000c00 |
|
VISUAL
cropResistant
|
8d9983e6a6a686a6,a8d4686969696904 |
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 895 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)