Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C813DC71AA24A87316F3E1C4D431BF5E35D3F31EE60A840A67F8968A1FC3DE5B9114A1 |
|
CONTENT
ssdeep
|
768:ugD8YbxvxTx3xwxGxXxvxDxAxUxQxbxxxdxfxU8YbxExQkxUxoxhxnxvxyxoEW:ugD8YbxvxTx3xwxGxXxvxDxAxUxQxbxN |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c2abbb8c8ca3a3ac |
|
VISUAL
aHash
|
ff006d7070600000 |
|
VISUAL
dHash
|
4b49c9c1e0c00101 |
|
VISUAL
wHash
|
ffeded7d70700000 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
4b49c9c1e0c00101 |
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 732 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)