Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T159C1DE10B000046B73B75FE0BEC4BE4A75A2F34AE50A8620D9A582994FDFEF17834DB1 |
|
CONTENT
ssdeep
|
48:s7DgDh9lupvvRKq57QH3obqyZDmL+1/4iK+1UtrfMj65cL2qHocQ:Plul0gm65pHUtrfMj65c6qHocQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
99996699993366cc |
|
VISUAL
aHash
|
1c18181c18000000 |
|
VISUAL
dHash
|
3232303ab2040010 |
|
VISUAL
wHash
|
3c3c1c1c38380018 |
|
VISUAL
colorHash
|
38003408000 |
|
VISUAL
cropResistant
|
0000104c4c081008,3232303ab2040010 |
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 9 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)