Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12AE239B4A230D335B1C24BE8DA642528765FE1DCD3C695B4F388AF51B0D6CE8D9260CB |
|
CONTENT
ssdeep
|
384:Y7fUtegu6TmLRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsiORWkMd:Y7fUtegu31hhPhleMeDGCSPxeeWmHLW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c3393ffc6815384c |
|
VISUAL
aHash
|
00242070f0f67670 |
|
VISUAL
dHash
|
4cccdac1c1c4ccc1 |
|
VISUAL
wHash
|
802620f0f0fefff0 |
|
VISUAL
colorHash
|
30600018000 |
|
VISUAL
cropResistant
|
69e8f0b9f8686868,88304c4d4c300882,4cccdac1c1c4ccc1 |
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 69 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)