Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17B23A5795107282B664BA7E0F5AF970C55AF4288EB07441DB67D4AB62BCCCF8D23F460 |
|
CONTENT
ssdeep
|
768:60pqBAGJb0oDpJEY88JPm6SAckvdmjRvK98tympy0NAQ6zrxuDuxCW1x1alg9/W4:60cBAGJb0oDpJV88JPm6SA2K98tympyP |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9933739c66663326 |
|
VISUAL
aHash
|
0018181818181818 |
|
VISUAL
dHash
|
3233727230b2b2b2 |
|
VISUAL
wHash
|
181c3c3c3c3c3e7e |
|
VISUAL
colorHash
|
300060000c0 |
|
VISUAL
cropResistant
|
3233727230b2b2b2 |
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 48 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.