Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12EB29AF2B420546303B3A9C4E5B1FF6EB696F30F811A84955EAC84921FC7CF9B542A74 |
|
CONTENT
ssdeep
|
192:6GVRKKE6qV4tuanD08u6QVshsX9q8Fhc48JhvG83VxuFdFeF0FDM/DdLBSGiix3M:HszADYFdFeF0FDMbW+6qze9 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
db3265663331cc99 |
|
VISUAL
aHash
|
003c3c3c3c3c3c00 |
|
VISUAL
dHash
|
0e69616969617986 |
|
VISUAL
wHash
|
033f3f3f3c3c3c00 |
|
VISUAL
colorHash
|
07001200058 |
|
VISUAL
cropResistant
|
8ec042434e015130,0e69616969617986 |
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 24 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)