Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D9F264B34100553F4323A7CAF4217B5ED093830FCA9698A4A3AD87475BD7FE5866DC2A |
|
CONTENT
ssdeep
|
768:XeJghtQIkS3s759jxANz+W4p8KCtbvmwdrPA/7re3xfUand+0K7lJBEtBEdgo:XeJghtQIkS3s759jxANz+W4p8KCtbvmJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
936c6c936c9392e5 |
|
VISUAL
aHash
|
00000e0e0e0e0c00 |
|
VISUAL
dHash
|
4218dc5858585801 |
|
VISUAL
wHash
|
e70e7e2e3e2e0e01 |
|
VISUAL
colorHash
|
31040006000 |
|
VISUAL
cropResistant
|
465778600d1e0080,4218dc5858585801 |
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 1021 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.