Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10CE229B4A230E335B1C247E8DA64256C7A5FE1DCD7C695B0E388AF51B0D6CE8D9160CB |
|
CONTENT
ssdeep
|
384:Y7kUteguLIc4waRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsOmRW+M9:Y7kUteguLuhhPhleMeDGCSPxeeWmHRI |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c723fc264833496f |
|
VISUAL
aHash
|
001620603036bed8 |
|
VISUAL
dHash
|
345442cbc3e86c33 |
|
VISUAL
wHash
|
80363e70383ebfd8 |
|
VISUAL
colorHash
|
30e00008000 |
|
VISUAL
cropResistant
|
e3e2e7aca7c0bede,80100c4c4c081000,8080c0e0e0f0f0f2,f2f2f8fcf8f8f8f8,345442cbc3e86c33 |
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 74 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)