Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AC72ED10A096566754B3C0C3F3F6AF3AA2D5D0A4E36B054493FC4B5F1BCBC28ED1A556 |
|
CONTENT
ssdeep
|
384:KuSdlO/ze4obvw3chRRiqvk7luz8f7r/o:NSrZfkhuz8jrw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
99cc999b66666623 |
|
VISUAL
aHash
|
181800180c0c0c1c |
|
VISUAL
dHash
|
32b2283039696938 |
|
VISUAL
wHash
|
3c3c183c3c3c3c3c |
|
VISUAL
colorHash
|
07c02000000 |
|
VISUAL
cropResistant
|
e4b0a4a5272b73f8,32b2283039696938 |
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 23 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.