Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T114B2CCB8514098736653CEDB7832275E71CEC619C80B79F58BAC83C71FEAE42892574E |
|
CONTENT
ssdeep
|
768:kbZuY15s5H5HIQBegNOSDZ1DUHuMkC/59vtmw:ZjDekC/R |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ee3b3bea50c5c490 |
|
VISUAL
aHash
|
8080fffbdffbff00 |
|
VISUAL
dHash
|
293be683b3b68304 |
|
VISUAL
wHash
|
8080fbf8d9fbf900 |
|
VISUAL
colorHash
|
070020001c0 |
|
VISUAL
cropResistant
|
293bf683b3b68384,3145696969690d99,0b4b0b0f0c0c0c0c |
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 278 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)