Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18023C9F9232853AC554B96DDEF30A1D8635FA0FABA6B84D0866F8B7495C7DC4E907C00 |
|
CONTENT
ssdeep
|
768:mwDsAZuShsxziC++GcI+0jV5lXro/iC++GllItSvQneim:mwDsAZ9/CTB0LlbvCTwiMoK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
94cd1cf372a6499c |
|
VISUAL
aHash
|
00ffffe7ffff7f00 |
|
VISUAL
dHash
|
c4b2324c4c63f4b4 |
|
VISUAL
wHash
|
00fef8e0dc0c0400 |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
e433b24c4c30e5b4,000018c5c5200000,41102cb2b2340841,3cb4b4b402818310 |
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 6401 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.