Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16BC1957060447B235186A2C4737A3B8AE2D18206C6560F59A2FDC3BD1FF6D44CC6BEE5 |
|
CONTENT
ssdeep
|
96:7MW71nusMSJSJSJSWefmQfmpRdvYFnSvsfQL9otMhhNgUhwW6s6De:7MA1/444WefmNESvsfQRotMupDe |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
83aaa8e8eacac8db |
|
VISUAL
aHash
|
ff003c3c3c3c3c00 |
|
VISUAL
dHash
|
31dcd0ccc8f0f0f0 |
|
VISUAL
wHash
|
ff1c3e3c3c3c3c00 |
|
VISUAL
colorHash
|
1b0000004c0 |
|
VISUAL
cropResistant
|
0049393131390126,dcd8d0ccd8f0f0f0 |
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 211624 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)