Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12982076503486B3D6513C6ACF7A6F324535EC1EEE27AC648F6ED02B252C3C45D9336A4 |
|
CONTENT
ssdeep
|
192:0sxzY9XYk5Fm0mYjEYqxzOOe5ZoD7AXRUxAHjYQNjywAcQSyUZxBcFL/W:00zYlYkmYYYOzhq+AkwjYk2NjaNcFK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
dd0af622d48ad78a |
|
VISUAL
aHash
|
ff0018000000ffff |
|
VISUAL
dHash
|
4130683230680d08 |
|
VISUAL
wHash
|
ff003c181800ffff |
|
VISUAL
colorHash
|
02000000e00 |
|
VISUAL
cropResistant
|
6100107068303268,118a88aaaa888a11,9292929292969210,0000300c4c0c0c02,0030707032306004 |
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 12 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)