Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18003B9A1610340B347B79AD1F1707F1F71A6F30F870E89593AA8C1662FC7CB5B612A69 |
|
CONTENT
ssdeep
|
192:62VRjLgZ2uTFB9FUFCFrF/FD+FfMgl5hMB0ABgvjbe1sCPJz7igEr5fQYRyv7ybN:vMZ2uTFLFUFCFrF/FD+FfMb19xLIt |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9999999999999999 |
|
VISUAL
aHash
|
1818181810181800 |
|
VISUAL
dHash
|
b2b2323030323230 |
|
VISUAL
wHash
|
3c3c3c183c3c3c3c |
|
VISUAL
colorHash
|
38007000000 |
|
VISUAL
cropResistant
|
bcb8a1e4a4e0e8bc,b2b2323030323230 |
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 10 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)