Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T141E1A72662241E3D262702A6F595B32CD19AD35EC21B997DF27C23F65B82DC1C8772D0 |
|
CONTENT
ssdeep
|
96:TGoMBMVH4Tn0XeA+032QUBJrkYIJafWDkaEHHmDkmQDkxYPp0JmkYbwO:aoQ4H4juNTGQUrKDKGD/QDusDdwO |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b8344bc7cfc60cb1 |
|
VISUAL
aHash
|
ff87879fcfffff99 |
|
VISUAL
dHash
|
63183820182e2b3b |
|
VISUAL
wHash
|
bb00849f8fcbff00 |
|
VISUAL
colorHash
|
07000000e00 |
|
VISUAL
cropResistant
|
63183820182e2b3b |
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 23 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)