Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13D23A9603485527722B3C6C9E6217F5931EEF31FE60A49446EFE85944FD3CF8B80A866 |
|
CONTENT
ssdeep
|
768:cOM1LH3M9e32Z1tAtdtYWKx0kxEtVzLzSz1zhmPuolvnL2umy7PsAFnhO4Xh:cxpie32Z1tAtdtXG0kxEtV/u5lmPuolR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ee49959466636a4e |
|
VISUAL
aHash
|
fffde1e1f0f5e7e7 |
|
VISUAL
dHash
|
8c31034765a54d4d |
|
VISUAL
wHash
|
fcf9e06010c1e5e7 |
|
VISUAL
colorHash
|
06006000040 |
|
VISUAL
cropResistant
|
8c31034765a54d4d,00134f8399191919 |
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 28 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)