Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DE521AB5722821B08E0343D7BE6123FEB213807DEA5297D8D358C21873959FD89B5EC5 |
|
CONTENT
ssdeep
|
192:QoRoBt504ElUik75h0hIzD6FUA43ku9cuGRmKbMpBXp7sfgg8gk:Qqou/yloIKWMsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72a552a552a5da8 |
|
VISUAL
aHash
|
81e7e7e7fffffffe |
|
VISUAL
dHash
|
4d0f0d4d0d712b22 |
|
VISUAL
wHash
|
0081e7c787ffb780 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
4d0f0d4d0d712b22 |
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 487 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)