Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T178C3FA20AD41EA1B12C786F57573A34AA3E58303D79207BCB5A167A4ABCFC44DD372B1 |
|
CONTENT
ssdeep
|
1536:mjlsIxQj0zhTeh24MFPIBS3SGaSSSSniz2Wpvb7UCl+0vzOiiFENxIh:mjlcj0zJmPuPsS2izdb7XaiGGu |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f6b1cb895c1c694c |
|
VISUAL
aHash
|
ffff420000000000 |
|
VISUAL
dHash
|
1b0d8e2c0ccb6561 |
|
VISUAL
wHash
|
ffffc7008020bdb0 |
|
VISUAL
colorHash
|
07007008000 |
|
VISUAL
cropResistant
|
3b33181a384d0e8c,0946b209852001e0,4080009098a890a1,40890090882a90a1,51792cd322902087,9c9e9298e4d8dcd4,0060109080200000,8e0c2c8ecb4c6165 |
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 4640 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.