Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16CD33312314868B7427BE5C1EC157F0A35D6B2EFA62E860152FC26A8AFF3C70F715661 |
|
CONTENT
ssdeep
|
1536:vZW04OUEM9k6FdRTu9MrUXUwKFTDpjMae6FdRTu9MrUXUwKFTDpjMa86FdRTu9Mj:T3xhxu0rvW7hAM8603c22QNE |
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 1450 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)