Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10BC173341A566A2F63278BB0F891775894EEA30FC5128815F2FC03575FDADE1CD26B21 |
|
CONTENT
ssdeep
|
96:TGvKSWxXZ1JabJJEJxNrEEw3NvtEwAckJ93DLqQue5d9rUDWRlVhueyNheufhCuz:aqx7FrrcmBwQd9ZQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a36e4d666309dc33 |
|
VISUAL
aHash
|
00e7ffe7e7ff7a7f |
|
VISUAL
dHash
|
170e080c4c00d6d6 |
|
VISUAL
wHash
|
00e7e7e7e7e70042 |
|
VISUAL
colorHash
|
07000000e00 |
|
VISUAL
cropResistant
|
170e080c4c00d6d6 |
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 12 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.