Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15C233570A00081A383A7D7E6F0A07F5A7696F70FD40E96467E6942911FD3DEC7A2E1B1 |
|
CONTENT
ssdeep
|
384:TOMw2qR7MHhrJnjduVQxLSAp5IM3dq5wHSi49bfLiM:TOMw2qR7MHra |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc999933333236ce |
|
VISUAL
aHash
|
1838180000001818 |
|
VISUAL
dHash
|
32b2b23220203232 |
|
VISUAL
wHash
|
3c3c3c3c183c3c3c |
|
VISUAL
colorHash
|
38206008000 |
|
VISUAL
cropResistant
|
e4c8e8aceda524cc,1d182b27b0c982b0,32b2b23220203232 |
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 28 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.