Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14492BC35660000AB03B799C1F6607F1FB6D3F30F821A8552ABBE919A1FC3CB577A1562 |
|
CONTENT
ssdeep
|
384:gM80xSQXRtFvXWptFw1l3sM1tBREMXZF7CZV101klE+kGTBWsGavOuKaq1uDKDV4:gsIrM1tDk |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3333332cccccccc |
|
VISUAL
aHash
|
c3c3ffe7effff7ff |
|
VISUAL
dHash
|
0e0e060c0c0c0404 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07012000200 |
|
VISUAL
cropResistant
|
0e0e060c0c0c0404,000000008001a280,9229ebcbeba305e1 |
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 26 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)