Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C17386B13D92582A615F52CBE2AB260E62C2C3C4CB51569563F4C32D8EF9E40F9E3E54 |
|
CONTENT
ssdeep
|
1536:K7ekpELJ7m7+IPmmJgzSVoTjx1Q+5pScbd4+5pQc16KjtfzS3JH+IPmmJgzSX+T8:KEVVVc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b01b0cf2f33d1c8e |
|
VISUAL
aHash
|
0f1f1fcfc7c7c3c3 |
|
VISUAL
dHash
|
b4f4b49e8d9e9696 |
|
VISUAL
wHash
|
0f0f0f07c7c3c3c3 |
|
VISUAL
colorHash
|
06006000000 |
|
VISUAL
cropResistant
|
d0d0d0fc34fc5d1d,0202020202020202,11271787604cfc7f,6dbd2d4f434f4d49 |
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 7 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.
Pages with identical visual appearance (based on perceptual hash)