Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C1442BF4936853F096474BE4F9711A46335910FEFB914A88C3A18EE0FAB2DC9D479CA1 |
|
CONTENT
ssdeep
|
3072:eXDGTa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1DY:Ah7jDw/47g7/t4 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce6131ce82a7cf31 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
8c3b69696969690c |
|
VISUAL
wHash
|
40003d7ffffd8504 |
|
VISUAL
colorHash
|
31001000e00 |
|
VISUAL
cropResistant
|
8d9987e6a6a686a6,8c3b69696969690c |
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 633 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)