Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T133F242705154AA3F81D7C3E5E7343B2B23E483C9DA6B165B93F883684F82D85EC27994 |
|
CONTENT
ssdeep
|
192:53tjxvWPjIQg/7kbbbC3OCc7TzoknqAgVqA2qAStaqAbqAbqAMqAvKYqqAxlqAZu:5dxMIQg/7kbbmeA41w |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ea694590bababa94 |
|
VISUAL
aHash
|
000081c1ffffffff |
|
VISUAL
dHash
|
49c0233bc0616860 |
|
VISUAL
wHash
|
00000081ffbfffbf |
|
VISUAL
colorHash
|
0e0020001c0 |
|
VISUAL
cropResistant
|
2161409061674180,82828aecacaa0082,2333c06168686860,20d09ce2c2c20c40,d4d456565252d4d4 |
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 457 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.