Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CCF0DDD021407A22177343D0058BD73672E14A66C74E160007E992F406FCF59DCC21C3 |
|
CONTENT
ssdeep
|
12:hRwMy7FUMbwF+aUcbpaPK4u+tT6Rk3gYQ9EmggdgWQ:hR/ClwnaPKCT6i3EdgWQ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc3333cccc3333cc |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
1000303030300000 |
|
VISUAL
wHash
|
0000181818180000 |
|
VISUAL
colorHash
|
38007000000 |
|
VISUAL
cropResistant
|
1000303030300000 |
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 2350 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)