Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10334A87C300215AF6177CAC0B4A1BF0AE0E2F30BDE69E605D5EE12156FDBD2269E1674 |
|
CONTENT
ssdeep
|
1536:29TkRoHf4jJ8rBKish6WMItgFzEuDTzwvN9Tav1t4tBrl1Vp/7FUZL8R+7fU0HBM:22RoHf4jJ8rBKish6pKgFHoFUZL8R+7u |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc3633933389dc |
|
VISUAL
aHash
|
0018383818180000 |
|
VISUAL
dHash
|
0fb5737370734541 |
|
VISUAL
wHash
|
85f83d3d3c3c3d20 |
|
VISUAL
colorHash
|
30200038000 |
|
VISUAL
cropResistant
|
e5e1b0d6d47170c8,0fb5737370734541 |
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 66 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)