Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BCC3E7A17010287B911F79DEB2167F4E622FF32DEA6DC060ADED4AB867E1DA5F401407 |
|
CONTENT
ssdeep
|
1536:HAg2S3gm4Yzjb00V8xPFjbXOQFk8GAXoXWF/FthtUtEtJpYuGgJot+tei6t3HeSB:2XYeSMJYiTVCL |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ea69ce39c2123796 |
|
VISUAL
aHash
|
000000000000ffff |
|
VISUAL
dHash
|
93030c71c91b244c |
|
VISUAL
wHash
|
00216710e781ffff |
|
VISUAL
colorHash
|
070010080c0 |
|
VISUAL
cropResistant
|
30c4e4246466084c,99130c0669490f13 |
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 134 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)