Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T122A13214B245950B2223D4D0D593DE8BF6D7F70ACA0AED0487BC23A56EDFD21BE50E64 |
|
CONTENT
ssdeep
|
96:dzlSPvRKFEHG91G9nGln7lEvSseaxu4UTaxuiInurqxF/E61ueWGDYFWGoLWGpLR:5U3E59M9GySYVilAWpv9L1SS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b9114e4e7b31334e |
|
VISUAL
aHash
|
00ffefef0000ffff |
|
VISUAL
dHash
|
b0a4199964100000 |
|
VISUAL
wHash
|
00d7cfcf0000f3f3 |
|
VISUAL
colorHash
|
07030000200 |
|
VISUAL
cropResistant
|
e835b4619999610e,0000000000000000,0001014341434380,0008303232322c10 |
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 10 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)