Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1800484307501482F2EAB53C47918EA1BE6C3F30DC5EE65C53BB847523F838A76A5B664 |
|
CONTENT
ssdeep
|
3072:i+QCpQYkqOmp4QWCmPp7iL6Ip4QWCmPp7iL6BT:i+QCpQYkq8 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cd4933c39c953173 |
|
VISUAL
aHash
|
7ee199d999f9ff9e |
|
VISUAL
dHash
|
92033333338b0630 |
|
VISUAL
wHash
|
0cf9899999f9838e |
|
VISUAL
colorHash
|
07000000038 |
|
VISUAL
cropResistant
|
92033333338b0630,845c5b23555571ea,213c1c5161647421,010024b2b2b20c10 |
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 257 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)