Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T149143B643655F92757FB42D640AB8002F339156A180D083CFB78ECEA756898A70BBFF5 |
|
CONTENT
ssdeep
|
3072:vKXc+7zRYGimXJXJ5JXJmJBJBJEJ4JUJZJPpYGK6coZMXjUMAL98n0AV8Fg:vec+7zRdimXdPhoz/uaebHs2ZMz458nh |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
887722dd22dd8877 |
|
VISUAL
aHash
|
1818181818181818 |
|
VISUAL
dHash
|
3232323232323233 |
|
VISUAL
wHash
|
18183c3c3c3c1819 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
3232323232323233 |
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 11 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)