Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16EF295B34000553F4313A7C9F4217B49D093830FCE9698A8A2AD87975BD7FE5866DC2B |
|
CONTENT
ssdeep
|
768:kwcghtQIkS3ha59jxAzN+W4p8KCMUb9W5l4dk7re3xw/LGB0K7qJBEtBEdgYIpS:kwcghtQIkS3ha59jxAzN+W4p8KCMUb96 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
93566d936c929356 |
|
VISUAL
aHash
|
00000e0e0e0f0f03 |
|
VISUAL
dHash
|
4218dc5858585b03 |
|
VISUAL
wHash
|
c30e7e2e2e2f0f03 |
|
VISUAL
colorHash
|
31040007000 |
|
VISUAL
cropResistant
|
1252d23002472b0d,4218dc5858585b03,016928174d30b10d |
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 561 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)