Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12A735F78272C3E6D681BC7A4FB65FB69132C5190F95EE0AC95BC663026C7CC4BC27984 |
|
CONTENT
ssdeep
|
1536:zLfETTTTbfbgaPhnWAFuOqk39DDDDQDDDDDDDDD2DDDDfDDDDvDDDDYqDDDD8DD4:fHw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d52a552a552b552f |
|
VISUAL
aHash
|
0000fffffffffffe |
|
VISUAL
dHash
|
008000000000088a |
|
VISUAL
wHash
|
0000fcfcf0f0ff00 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
80a00000000008ce,0080010101418200,0000000141010000 |
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 230 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)