Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14262F8B5002448BB814B47A4EBA07B0C73BEF2CAE6754460D3EA86165DEBDF3D87D461 |
|
CONTENT
ssdeep
|
192:c8k6O6ExbMAUygOx7xgQYL23Eu89aJk+n7nCniVVw4YL23Eu89ktahUam4P:c8k6O64WQEw589aAiU4Ew589ktaa4P |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9818e71ee6e218e7 |
|
VISUAL
aHash
|
ff1f0f0f0f0fffff |
|
VISUAL
dHash
|
b9b4b4b4f4347070 |
|
VISUAL
wHash
|
0f0f0f0f0f0f0f0f |
|
VISUAL
colorHash
|
07032000000 |
|
VISUAL
cropResistant
|
b9b4b4b4f4347070,7374eed595ef262e |
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 5 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.