Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D665E4B14301405E4FC1BD94F0653D0F1872F2D6EE2E14D9A7A5291CBEE1BDAA5E02FA |
|
CONTENT
ssdeep
|
1536:5FR4xfzoOemeHTKwODawxhMaNghmRRSzTXth0vFdF+ZOYdJTmNgid7BXC7Or7cAt:5G6csBPqqqNgbB/89 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9ff849e3608f4ac8 |
|
VISUAL
aHash
|
00879f9fef2f3f00 |
|
VISUAL
dHash
|
316e706c8d4c6475 |
|
VISUAL
wHash
|
00871f9fef2e3f00 |
|
VISUAL
colorHash
|
06048008000 |
|
VISUAL
cropResistant
|
00d3c15959c3830c,2c7a640c8d4c6465,00000607160010b4,6535755551510303 |
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 445 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.