Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11A443BF4936843F4D6474BE4F9711A56335910FFBB914A88C3A18EE0FAB29C8D479CA1 |
|
CONTENT
ssdeep
|
3072:epD1Ta7jDw/4Q1pSBn1pSBy1pSB61pSBo1pSBafoi2cluAkYc1DV:s07jDw/47g7/t1 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9a3065cbcbcace34 |
|
VISUAL
aHash
|
00003c3c3c3c0000 |
|
VISUAL
dHash
|
aa9c796169693103 |
|
VISUAL
wHash
|
001e3e7fffbd8100 |
|
VISUAL
colorHash
|
39000000e00 |
|
VISUAL
cropResistant
|
c0c0d0c080808080,aa9c796169693103 |
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 629 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)