Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A50340309000983742E3E2E2A635675BB3D2834CCF531FA566F8C75E9FD6DA4ED12A64 |
|
CONTENT
ssdeep
|
768:V+Y0Ae8YXHPMlXKCTZMYDsCeeeAOfHBtpxuGcGVQl0SUrjHRupUf7zd4BJ0w8:V+Y0Ae84PMlXKCTZMYDsCeeeAOfHnROC |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ccb7a149b2696665 |
|
VISUAL
aHash
|
40fef0fef0f0f8fe |
|
VISUAL
dHash
|
d982222420609380 |
|
VISUAL
wHash
|
40f8f0d4f0f0f0fc |
|
VISUAL
colorHash
|
07400008080 |
|
VISUAL
cropResistant
|
d982222420609380,0000000000000000,000844a4a40a8000,34326070343545c0,2000000400041818,c02120129bc34b48 |
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 44 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)