Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17E633F24B10146FF46A7C9E0F1607F1962EAF34ECB6BC954A7AC50A16FCFCB07A115A1 |
|
CONTENT
ssdeep
|
768:wBLoLPWrtM4M7UbYozj48Dr3QBcrnMBARX3dkDTb9byTbVb5bYbIFMyPBVMhe7KK:dTxGT5Ns0hPB8ew4nQ5xmV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
842a3b3acbeaaa3a |
|
VISUAL
aHash
|
0102067636160662 |
|
VISUAL
dHash
|
931c94c4e4e40cc2 |
|
VISUAL
wHash
|
4106067e7e7e067e |
|
VISUAL
colorHash
|
38042001000 |
|
VISUAL
cropResistant
|
931c94c4e4e40cc2 |
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 57 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)