Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T152720865E22123719AC683DAEF2A63EFE31340D5D6116FCC9259821DF18C4EFC919EC1 |
|
CONTENT
ssdeep
|
192:Qo1oB6CJ54t94CiBGqj+8tj9fm7EIhD8ku9cuGRmKbMpBXp7sfgg8gk:QwoCg8EVm7rhDXsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
952a55aa55aa55ea |
|
VISUAL
aHash
|
07050f7f3f1f7f7e |
|
VISUAL
dHash
|
2c7ddfccf871c1d2 |
|
VISUAL
wHash
|
0701013f0f1f7f3e |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
2c7ddfccf871c1d2 |
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 485 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)