Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T133442BF4936853F096474BD4E9711A56335A10FEFB914A88C3A48EE0FAF2DD8D439CA1 |
|
CONTENT
ssdeep
|
3072:eeDRTa7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1D1:NA7jDw/47g7/tV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8e3131ceca6fce30 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
aadc686969696904 |
|
VISUAL
wHash
|
007e7e7f7fbc0400 |
|
VISUAL
colorHash
|
39001000c00 |
|
VISUAL
cropResistant
|
8d9983e6a6a686a6,aadc686969696904 |
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 593 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)