Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BB62867161101A3F26174BA8F199F729D09A8389C51BC47EF27C42F26BC7CA4C97E395 |
|
CONTENT
ssdeep
|
384:DD/XDMYKGjKlWtst9y5yM5Rt0zroCxVi8ONOBOg:DD/XD2lttM5yMrt046ViN4Mg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b7331999cc98cc36 |
|
VISUAL
aHash
|
e7e7e7ffe7ffdfd3 |
|
VISUAL
dHash
|
0d4d4d144d0e1a16 |
|
VISUAL
wHash
|
81e7e7e7e7a38100 |
|
VISUAL
colorHash
|
070000c0002 |
|
VISUAL
cropResistant
|
0d4d4d144d0e1a16,9e2e266666466666 |
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 82 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)