Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T147342AF5536853F096874BE4EE321A5133A910FFFB914688C3A18DE0F5B29D9E439CA1 |
|
CONTENT
ssdeep
|
3072:5XQ2Ta7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1D4:5XQx7jDw/47g7/tY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9b31644ecf1b9a34 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
d052796969696186 |
|
VISUAL
wHash
|
003c3cbc3c3c19ff |
|
VISUAL
colorHash
|
3a200008c00 |
|
VISUAL
cropResistant
|
f838303eae80a080,d052796969696186 |
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 645 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)