Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14AA3FE3CB1067C26647795C0F0946F997182EB3AC3448E58E3B527A62FCBDF468A5378 |
|
CONTENT
ssdeep
|
1536:LRvIc6MZhK7fKB/OcDagwp3FcQ8Ev5kv/J//oxvHbuMAHL60grkLhLYN2OyZUw2/:EMPMCxKAMc8So |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f72266cc88dd885d |
|
VISUAL
aHash
|
e7e7e7ffe7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d0c0c0c4c4d |
|
VISUAL
wHash
|
0404040427272627 |
|
VISUAL
colorHash
|
072000000c0 |
|
VISUAL
cropResistant
|
4d4d4d0c0c0c4c4d,691329696963aa74,64a4a4a4e498a8aa |
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 507 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)