Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1140444974328A2EE78DBC9FC694FB229D10AD087E0F2548EA1DD8675C747CD1DB26780 |
|
CONTENT
ssdeep
|
3072:IDvBMugYKfjxhBMugYKfjx83zszfGvTmq3zszfGvTmKi:yBMugYKfjxhBMugYKfjx83zszfGvTmqY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9111ee6ecace6e90 |
|
VISUAL
aHash
|
ff0e0e0e0e00ffff |
|
VISUAL
dHash
|
439c98d898a7550d |
|
VISUAL
wHash
|
390e0e0e0e00ffff |
|
VISUAL
colorHash
|
060000001c0 |
|
VISUAL
cropResistant
|
0041515153c5008a,fc7866446060c1a0,4c0855550a100c0c,9a9c98d8d8d89827 |
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 15 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)