Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1FA736CF4F4A1EF3382B302C594AB1196323554069D0A09F5B6C8EFDF66D6C95B82B6CC |
|
CONTENT
ssdeep
|
768:WUj1VrgGcP/nwM/MF6HIDhpsfpPP+y4c7vMlI9UfqzdrRHcyMBWk2sClYQg/A:N1Vp09oc7I6rRqQR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bb19e4d4cce4c1e1 |
|
VISUAL
aHash
|
ff0f0f0f0f0fffff |
|
VISUAL
dHash
|
b85adb5b5b5b044c |
|
VISUAL
wHash
|
0f0b0909090ff7ff |
|
VISUAL
colorHash
|
17000200030 |
|
VISUAL
cropResistant
|
b85adb5b5b5b044c,0f32716970f8b0cc |
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 327 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)