Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T113032D307501546742B3AAC6EA61BF1EB2D3F30FC64588619AED009A5FD3CF5BC3A4A4 |
|
CONTENT
ssdeep
|
384:eAmbx1RDpWm8E1l37IT657JMxc4LgOGowhKAVtT7qhPOaszhGqyVaT83jfTx+P:eAORrLLMxc4LgOGJhNT7qhPVAhGqD |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
d9cc666639199933 |
|
VISUAL
aHash
|
1038181818181018 |
|
VISUAL
dHash
|
21a2b2b232b23032 |
|
VISUAL
wHash
|
9838383c1c3c3c3c |
|
VISUAL
colorHash
|
38010200048 |
|
VISUAL
cropResistant
|
231b39b2d9f19dce,80280c0606144880,21a2b2b232b23032 |
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 221 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)