Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14E833921E100563C2F6B8BF8F056A61FE2969D0FF7516871F96D63E35483B648BBB018 |
|
CONTENT
ssdeep
|
1536:LSYwbgtX8/shG9QITUObIfVu9ZfVkNYj5KFr2PcJpIyeaqq6nkuewz3ajisp74n8:LpM2eaqq6kuFjajispMn3OXE+GnIWnIh |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b847c7383ec7c0cc |
|
VISUAL
aHash
|
ffcfdf8d8fcfffff |
|
VISUAL
dHash
|
881b39393919060e |
|
VISUAL
wHash
|
7f898888888dc3ff |
|
VISUAL
colorHash
|
07c01000000 |
|
VISUAL
cropResistant
|
881b39393919060e,79f547123f6c6703 |
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 1042 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)