Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DF62F77231A127AE049787B9F5C4A32C9166A61DF963E890D39F022A1FD2DE7CC745CC |
|
CONTENT
ssdeep
|
384:ExuNtkFfk7cXbEREK7wDNBSbOoynG0g7blIQ:ExuNtkFfMPEuSNBSKxc7bKQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3e3cc1c38c3333c |
|
VISUAL
aHash
|
ffffe7e38183ffff |
|
VISUAL
dHash
|
80004c0f2f2b00a0 |
|
VISUAL
wHash
|
4fcfc3810101fd7c |
|
VISUAL
colorHash
|
0700b0000c0 |
|
VISUAL
cropResistant
|
80004c0f2f2b00a0 |
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 222 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)