Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B5F16930A144DC73509385F5A735AF6F63C1938ACA83861396FCA75E8FDEE90CC2A465 |
|
CONTENT
ssdeep
|
96:tnar/HK1ZeZFZ4BZUZCZpWpBxBnc8n8vbNBw84v2jTfeZbZ6:mf+WZbZ6 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b93939ce86c686c6 |
|
VISUAL
aHash
|
0181ffffffffff0f |
|
VISUAL
dHash
|
3b3b3bc46979415a |
|
VISUAL
wHash
|
018181ff3d3dbd0c |
|
VISUAL
colorHash
|
060032000c0 |
|
VISUAL
cropResistant
|
3b3b3bc46979415a,78787c78785c5878 |
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 55 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.