Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B6D32321C6A41333D205078AE3EB7756679BC1C7CC92B8F8A1608175DBBED891C77DA2 |
|
CONTENT
ssdeep
|
3072:S0KJrjylK2E6IOZuagKI3ImJS20gIYLQICeIkPksuGIyIhuBnvmf7m:9KNQ5IZf3NSfq |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f352ada78398683c |
|
VISUAL
aHash
|
ff80000020e3fffb |
|
VISUAL
dHash
|
4b1899584c4e3293 |
|
VISUAL
wHash
|
ff80808020e7fbfb |
|
VISUAL
colorHash
|
0f601008040 |
|
VISUAL
cropResistant
|
4b1899584c4e3293,e636723869f4f2d1,0020d0d0d0d02040,983929b898989a9e,9f8d8d8c8f233265 |
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 27 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.