Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T128B1C7B22159193BA71381F1B9D6F75580A9C71DC01FEA10E3EC02BA2FC6E85CD7B664 |
|
CONTENT
ssdeep
|
96:Th0CES50CN0CB46Yb4tw27pBfY6H8DGVK3+IKl6rTVm7u3x6GiT3E7cnU:l0nS506078lbtGWS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f8320ffa6c2d4c0e |
|
VISUAL
aHash
|
0005c0c2f0f80010 |
|
VISUAL
dHash
|
1999969680917263 |
|
VISUAL
wHash
|
01cdc2d3f8f8be18 |
|
VISUAL
colorHash
|
1be40000000 |
|
VISUAL
cropResistant
|
5f7b19273511618c,1999969680917263 |
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 16 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)