Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F7832A31E101953C1B3F8AF5E42AA567D3569C0FFAA218B1F96D63A771C3FA08B27015 |
|
CONTENT
ssdeep
|
1536:LsnFw9QXF/Sho2ha3SHtXLGZfT0ZNqcQnaqq6lySAZHEit2lXMVDgzGryqyajis3:LzMaqq6MSXajispDn3O8E+GnIWnIjiD2 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b847c7383bccc0c7 |
|
VISUAL
aHash
|
ffcfdf8d8f8fffff |
|
VISUAL
dHash
|
881b31391919260e |
|
VISUAL
wHash
|
7f898888888dc3ff |
|
VISUAL
colorHash
|
07601008000 |
|
VISUAL
cropResistant
|
881b31391919260e,430b0b891963333e,260e1e1e2d8d9d39,6d67e7eb67635b7b |
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 1301 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)