Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14BB2B6F2111019BA5B0347DEE8D6360DB34FA609EFD1A4908B7A46F466D7DB6F00E826 |
|
CONTENT
ssdeep
|
384:Tu+BVlhceWX5VtN7CweXRFDnvzcoUdiYZjJtmsP/Bne:CI/hcFNehFrzZUiYZ5PQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
aaaaaaaaaaaaaaaa |
|
VISUAL
aHash
|
1962010000000000 |
|
VISUAL
dHash
|
318a010800000040 |
|
VISUAL
wHash
|
193e3e3e3c3c3e00 |
|
VISUAL
colorHash
|
38000000000 |
|
VISUAL
cropResistant
|
318a010800000040 |
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 333 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)