Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1854142323100692B2673B3D854A15B2E1AE2D329CD031A9876F4D3ED9EE6EE8CC71134 |
|
CONTENT
ssdeep
|
24:hIbwOuNYPpNaYW/n7kSeAli6iwvKnNVkkNVKkSeAlJbvgVhNSK+KVKiKQo2:+b3u6PpdvD6/KNLRvQqPjUXQz |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e632339966669933 |
|
VISUAL
aHash
|
e7e7e7e7e7e7e7e7 |
|
VISUAL
dHash
|
4d4d4d4d4d4d4d4d |
|
VISUAL
wHash
|
0707070707070707 |
|
VISUAL
colorHash
|
0e007000000 |
|
VISUAL
cropResistant
|
0000000000000000,0000000000000000,62d8c38a88d01034 |
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 65 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.