Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C282FBB190107133081B8EC9757A930FB4FBA65CCBBB4D142BBC97D96BC3C988E15906 |
|
CONTENT
ssdeep
|
192:fYvOeOG1j++9yVxhM+OGZ7u7DvYtf/5b6tXqncHbj1/Kwu:fYvZrF+eyGbGZ7iDvwfBetXqngf1/K5 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
bf3b1e4ac1444fc4 |
|
VISUAL
aHash
|
008183ffffb5ffff |
|
VISUAL
dHash
|
793b1b135975659c |
|
VISUAL
wHash
|
00818183fda5bdff |
|
VISUAL
colorHash
|
06016000000 |
|
VISUAL
cropResistant
|
0200020200020282,3b3b135a51652559,6969861b1b1b2b6b,1f404342c282aa0a,163332869622a212 |
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 11 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.