Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16973F7F4322852AE104747D9FF71FA98639FE1AEF556C49099AE43A817C3D94ED23840 |
|
CONTENT
ssdeep
|
1536:H6bq2xGP9QJ0vmF2pNP9I+yOU7bKNIkl/L2oMl6zCeGAxL3qlyY:v7pnJCkQ8z5L6D |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b3666619c3cec722 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
0c0c0c0c0c0e0e0c |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
0f0000001c0 |
|
VISUAL
cropResistant
|
0202020202020202,a0a0a0a0a0a0a0a0,06a2aa3355bc5755 |
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 233 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.