Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A5D22735A601456B43B799C1F6717E6F75D3F30F80068606ABBC918A2FC7CB6BB60162 |
|
CONTENT
ssdeep
|
384:+M26j49FxF0F0FNbFiFO1FmFFMUo6kt+8:+JD88NhmOPyFMj3n |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
893333cc32cc66ee |
|
VISUAL
aHash
|
0118181800183800 |
|
VISUAL
dHash
|
1d12322020b2b24c |
|
VISUAL
wHash
|
011c181818383c00 |
|
VISUAL
colorHash
|
38400030000 |
|
VISUAL
cropResistant
|
21944b6b4646a048,728d6c4b4b568668,1d12322020b2b24c |
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 36 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)