Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E4E217796601456B43BB99C1F6217F2F71C6F30F81068545ABFC918A2FC7CB6BB60462 |
|
CONTENT
ssdeep
|
192:6hVRmvydsFHF6F6FNnF2FyJFaMTMx9s6+Atzp6dixQH0edrVhTTJeEMNzS+xAP6A:EYydsFHF6F6FNnF2FyJFaMctLkdlv+8 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e66666338c999999 |
|
VISUAL
aHash
|
c3c3e7ffffe7e7ff |
|
VISUAL
dHash
|
4d4d4c100c4d0c04 |
|
VISUAL
wHash
|
c3c3c3c3c3c3c3c3 |
|
VISUAL
colorHash
|
07000018080 |
|
VISUAL
cropResistant
|
4d4d4c100c4d0c04,09188ccea6824309 |
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 22 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.