Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14EF20F66C1629EBB0523D1C1EEA0AF2BF3810189CA670E4573F99B2B9BDFD44DC41647 |
|
CONTENT
ssdeep
|
768:jzY6uP2xm4oQURPbR9TUjaRRPhLFKNIIIIIo7e+FB+9k9YrCVsfmJZ2DwN63kxOu:jzY6uP2sZQURPbfTUjaRRPhLF4IIII7Z |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ce3466196731ce33 |
|
VISUAL
aHash
|
003c1c3c3c3c3838 |
|
VISUAL
dHash
|
6471717171717161 |
|
VISUAL
wHash
|
003c3c3c3c3c3cff |
|
VISUAL
colorHash
|
09000001e00 |
|
VISUAL
cropResistant
|
b9632aa8d598a207,9c7ce4ac5561271b,e9e9a49c8c125a99,b2e2f2b2a28a9cbc,6471717171717161 |
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 40 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.