Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A9342BF5536853F096864FE4ED321A5133A910FFBB914B88C3A18DE0F5B29C9E479CA1 |
|
CONTENT
ssdeep
|
3072:q+Y2Ta7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1D/:q+Yx7jDw/47g7/tf |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cf38304bc366cf38 |
|
VISUAL
aHash
|
00003c3c3c3c00ff |
|
VISUAL
dHash
|
c251616969696696 |
|
VISUAL
wHash
|
003cbcbd3c3c01ff |
|
VISUAL
colorHash
|
39400000c00 |
|
VISUAL
cropResistant
|
c280a4a4a4a4a4a4,f0f033133337f2f0,9496b2969496aaaa,f0606d6d6d71f072,f0f2b2d39ab2f0f2,f0f071717170f0f0,c251616969696696 |
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 630 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.