Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T107D2C879A60511A743B799C1F2617F1F72D7F30F80168516ABBC928A2FC3CB6B721066 |
|
CONTENT
ssdeep
|
768:pIkdbCbCj0oO0caqsh5VsFvOsO1Uv9OMq5wNMP:pkv9OMq5wNMP |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e6646466cecccccc |
|
VISUAL
aHash
|
c3c3f7e7e7e7e7f7 |
|
VISUAL
dHash
|
0606060c0c0c0c04 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07608000400 |
|
VISUAL
cropResistant
|
0606060c0c0c0c04 |
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 27 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)