Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1A24229BDB22411B2DE0383CAF97523BAA10391BEDA6216D8D759835473D9DFD8811DC2 |
|
CONTENT
ssdeep
|
192:QoWoB6CJ54t9rhpw5B/ANku9cuGRmKbMpBXp7sfgg8gk:Q/oCFK5lASsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f9aa45cb558a7438 |
|
VISUAL
aHash
|
f9cf8f9fcfffff80 |
|
VISUAL
dHash
|
6b1b38349864602a |
|
VISUAL
wHash
|
b88e8e8e4e7e7a00 |
|
VISUAL
colorHash
|
07003000600 |
|
VISUAL
cropResistant
|
6b1b38349864602a |
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 482 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.