Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EFF273735041593F031396CAF426BB49E193870FCF9698D8A3AC83571BD6EE5892DC2B |
|
CONTENT
ssdeep
|
384:4MCPfnBF8UBMMtoK0PSwPSHvN2/yqxg57IW:4MKB0K9SglIW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
93566d936c929356 |
|
VISUAL
aHash
|
00000e0e0e0f0f03 |
|
VISUAL
dHash
|
02585c5858585b03 |
|
VISUAL
wHash
|
c30e3e2e2e2f2f03 |
|
VISUAL
colorHash
|
31040007000 |
|
VISUAL
cropResistant
|
1252d23002472b0d,02585c5858585b03,016928174d30b10d |
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 561 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)