Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A063633094C27877457352D2A131670D61E3E24CEE230985EBFDD7A95BCECA2EC2C6A5 |
|
CONTENT
ssdeep
|
1536:sna4bREHfsGTzOxdYIzb2z4W8V7DXsxS91DaeDEFgpurMbaq2W3qyNMbFK9Q8/Wa:ozbQ4Ld8E3lg+sQd7NMb8WcIuN |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9353ec2c79972661 |
|
VISUAL
aHash
|
0000000c000fffff |
|
VISUAL
dHash
|
b689c9d8997fe00e |
|
VISUAL
wHash
|
0204640c4c3fffff |
|
VISUAL
colorHash
|
02007000000 |
|
VISUAL
cropResistant
|
dcfcfcde944a348b,998f7ef18e204c0e,b628c9c9d9999ffc |
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 3 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.