Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DB733068271C3E2C641BC7E4F7A5FB68132C9190F95AE1AC96BC66705687C84FC3B9C4 |
|
CONTENT
ssdeep
|
1536:6VDDDD8DDDDhDDDDfDDDDQDDDDFDDDDsDDDDD8DDDDhDDDDfDDDDQDDDDFDDDDsx:6n |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b18a4e319b4f649b |
|
VISUAL
aHash
|
ffffffffef420000 |
|
VISUAL
dHash
|
161606161c96b292 |
|
VISUAL
wHash
|
ffe7e7c7c7030000 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
0616160e169e1e96,96f0b462a3939492,0000000000000000,100830b2b2300810,0000000000000000 |
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 22 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.