Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D7823C7AB31833B5CA4343E6FE2523FAF22790AD9B5217DCD628435873959EC8531AC1 |
|
CONTENT
ssdeep
|
384:QuoCuYFlJ+zu14hyoATCvj7+5TrvsmMpBZ7eg/B:fo8FlihyoATke8m4/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9f6ac0c337381d8d |
|
VISUAL
aHash
|
00fc1f073fbfff9e |
|
VISUAL
dHash
|
4dc8362c78709132 |
|
VISUAL
wHash
|
007c1f070f1fff0c |
|
VISUAL
colorHash
|
07038000400 |
|
VISUAL
cropResistant
|
4dc8362c78709132,45c41b88a46b9045,ceb6b51434200a8e |
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 485 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)