Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C8C35294B26109BB19B799D4B564FF5AE5A6F30BC21BDA0873BC80431FCBC71AD116B0 |
|
CONTENT
ssdeep
|
1536:SkZB+ZB5JwDnZqc8lcSecfcmCcfc6vcgIcxscfcQLCWGmzu+x0D+M/MYMPhM5MHq:S2BwBbwDnaLCWGmzulqDs0+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a0552f7cb917e0a5 |
|
VISUAL
aHash
|
0300666e4e4000f9 |
|
VISUAL
dHash
|
a300cc9c9c841193 |
|
VISUAL
wHash
|
0300ef6e7e6404ff |
|
VISUAL
colorHash
|
38200030000 |
|
VISUAL
cropResistant
|
a28a54070b5482a2,a300cc9c9c841193 |
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 106 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)