Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16A91CEB091AAC9774197D2E1B7B7AB2F73D18249CA430A0267FDC39D5BD6D51EC06600 |
|
CONTENT
ssdeep
|
96:0Puq5S9mf3Q23tHVScVSFFwDozNFE7CFoA//:0PnS9mY79FPzNFE7CFoA// |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c7c73898ce673298 |
|
VISUAL
aHash
|
00043c383c2c0000 |
|
VISUAL
dHash
|
225d496061596200 |
|
VISUAL
wHash
|
003c7e7e7e7e3c00 |
|
VISUAL
colorHash
|
38000e00000 |
|
VISUAL
cropResistant
|
6c6227524e2e6a62,225d496061596200 |
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 486510 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.