Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13DE239B4A230D335B1C247E8DA6425287A5FE1DDD7C695B0F388AF51B0D6CE8D9160CB |
|
CONTENT
ssdeep
|
384:Y7kOtegu7G2VRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AssGRW2Md:Y7kOtegu7phhPhleMeDGCSPxeeWmHnW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c73338cc783e694c |
|
VISUAL
aHash
|
006660307078be98 |
|
VISUAL
dHash
|
4ccccac3e5e46431 |
|
VISUAL
wHash
|
a0666630787ebf98 |
|
VISUAL
colorHash
|
38206000000 |
|
VISUAL
cropResistant
|
85858a88da1a78fa,100c323232320810,4ccccac3e5e46431 |
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 74 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)