Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18DF3D7CC2B7069D589CC8BDB7F01B5A97827A0F6999288C8D09C4F5D55D3C2CBD4AE83 |
|
CONTENT
ssdeep
|
1536:5HdMTtdvsUKbEEEcFOHjcadUQjByQVfZzIZSc3PUKufpxBfPGrq+Y6q7dXdhR1il:58DL+l |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c68fd187c097c3b8 |
|
VISUAL
aHash
|
7f0000204034a4c0 |
|
VISUAL
dHash
|
e45614e984ecac98 |
|
VISUAL
wHash
|
ff030f717076c4e0 |
|
VISUAL
colorHash
|
30000000e00 |
|
VISUAL
cropResistant
|
a200c0d0d0cc00a2,82600a1b1b2c0282,e45614e984ecac98 |
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 2534 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)