Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A2142A983245F51757FB929640BA4102B339156A280D0C3CF6B8ECEB756498AB1FBFF4 |
|
CONTENT
ssdeep
|
3072:ULrX2wd9W/guGOKXhGDQAJXtTJFJXJmJBJBJ/J4JCJNJmwGQyiFFUV3gA:ULr+ouGOwhBA7Dhoz/5acryQy6UV3gA |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc4ab3a20e8eb39b |
|
VISUAL
aHash
|
fd00000000ffffff |
|
VISUAL
dHash
|
65307020200c2a2b |
|
VISUAL
wHash
|
ff00000000ffffff |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
0051516d6d510000,a280a43a1b808082,200c0e0c402a2b2b,0470603070202008 |
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 18 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.