Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12BB2B5B193997CEB561F4B9FF084BBF89041A34CD66F9BB4B25B8AC613DEC326401191 |
|
CONTENT
ssdeep
|
384:F3uQ4B4V01e29l8sxx+lpz7ClJSKUMz1u13kAu:F3up1e2Qsxx+lpz77bsQ3kAu |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc38c738e738c738 |
|
VISUAL
aHash
|
88181818003c1872 |
|
VISUAL
dHash
|
31b03030337032c4 |
|
VISUAL
wHash
|
9818181880bffff7 |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
a224532b2fd40882,ad8ccb9991dbcbd7,31b03030337032c4 |
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 178 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)