Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D7F37DF5325CB3B3165303E66076110732BA207FB9068D60E3D4DECAA7BACD9942BD95 |
|
CONTENT
ssdeep
|
1536:OOY/1RY/1e03hUR/+HALGqqLii6b1hJElUuRNka2wblHbJLwLIz9GguGOjjRnY:8bD8rX2wd9W/guGO+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b1644c9b9bcc3371 |
|
VISUAL
aHash
|
98c0c3ffe7efffc3 |
|
VISUAL
dHash
|
299696e4cdcd372b |
|
VISUAL
wHash
|
000042e7e7effbc3 |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
299696e4cdcd372b |
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 977 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)