Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10F74D7B9825512B256CBCBC5F8B25B1A37D3529FEA424758D3E48BE0BFE2DC5E421C10 |
|
CONTENT
ssdeep
|
3072:epDQkTa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1Dj:km7jDw/47g7/tD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a3035cbcbcace34 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
aa9c796169697904 |
|
VISUAL
wHash
|
001e3e7ffffd0400 |
|
VISUAL
colorHash
|
39000000e00 |
|
VISUAL
cropResistant
|
c0c0d0c080808080,aa9c796169697904 |
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)