Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1E5D33212314868B7417BE5C1EC157F0A34D6B2FFA62E960162BC26A8AFF3C70F715661 |
|
CONTENT
ssdeep
|
1536:VZW04OUDM9k66oRin9MrFXUZKFySCIpae66oRin9MrFXUZKFySCIpa866oRin9M7:Bxeueu0rvWShAM8603c24QNf |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
fc93926cc32dc139 |
|
VISUAL
aHash
|
ffffdfffc38181ff |
|
VISUAL
dHash
|
cc343c66070f2f37 |
|
VISUAL
wHash
|
fe9f8ff2808181c3 |
|
VISUAL
colorHash
|
06040006000 |
|
VISUAL
cropResistant
|
cc343c66070f2f37,161626a74f8e8667 |
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 1383 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.
Pages with identical visual appearance (based on perceptual hash)