Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B2028CE2D8E15833054B86E9A0B20BE5FCFB4128D9CF692067F857D717D6C81CA2DC26 |
|
CONTENT
ssdeep
|
96:T0Jo9lbH+3QOhKnbkslVDTeew3W0L4DTeew3WbLPDTeew3W0L4DTeew3WbL4DTex:J9Z+cPd9PdzPd9PdQPdzPd9PdQPdzPdJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bd3f5bc0c35045c6 |
|
VISUAL
aHash
|
0081818fffdbffff |
|
VISUAL
dHash
|
79713f3baab2b2cc |
|
VISUAL
wHash
|
00010181ffdbdbff |
|
VISUAL
colorHash
|
06007000040 |
|
VISUAL
cropResistant
|
0000000000000000,71373b7db2b2b2cc,84397b7171373f3b,00e040400000fc00 |
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 32 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.