Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E98264795044AA73031682C06C3AFB9DB3C6F66EDE730D55A2DD8D8DAAC7D69CC0061E |
|
CONTENT
ssdeep
|
192:6LyvOo8rMq3IJDYItZaE5ZXEDI9CRKIOn2n7bvma7LU6HQkmGJPdV+h89yNZ6ehX:6LMOo8RItwE3XEJRtPzv+4EIEd |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
be321c1c723cd99c |
|
VISUAL
aHash
|
83ffffe7e79b83ff |
|
VISUAL
dHash
|
3b0c100d0c33230a |
|
VISUAL
wHash
|
00c72727e78183e3 |
|
VISUAL
colorHash
|
07000030000 |
|
VISUAL
cropResistant
|
3b0c100d0c33230a |
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 12 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)