Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10BA45FB02480443B4293D5DC60776B1B64D2E325DB0359414BFA87B98EEAEE0DDAB3D7 |
|
CONTENT
ssdeep
|
3072:sdxVYC2ALkWTcJZSwKqdxVYC2ALkWTcJZSwKw:sYC2aLTcJZS6YC2aLTcJZSA |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
83f9fe464558b870 |
|
VISUAL
aHash
|
f87fff6820000003 |
|
VISUAL
dHash
|
505058d0c0c0c043 |
|
VISUAL
wHash
|
fbffff3970000003 |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
505058d0c0c0c043 |
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 279117 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)