Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T132A28D71A00255A786F3D8C1D660BF29B2B3F30FC546C6A67AEC41961FC3CB9B912275 |
|
CONTENT
ssdeep
|
384:mekvFhLF8FaFMF0FbFBF2yM7nGCr+Ly37:mekNUOE8hz2yM7nGCr+2 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b33333338ccccccc |
|
VISUAL
aHash
|
c3c7e7ffe7e7e7ff |
|
VISUAL
dHash
|
0d0d0c0c0c0c0c0c |
|
VISUAL
wHash
|
c3c3c3e703070303 |
|
VISUAL
colorHash
|
07000000c00 |
|
VISUAL
cropResistant
|
0d0d0c0c0c0c0c0c,0000000001010101 |
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 13 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)