Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17AE229B4A230D335B1C247E8DA6429287A5FE1DDD7C695B4E388AF11B0D6CE8D9250CF |
|
CONTENT
ssdeep
|
384:4r/aJcuvt8RvRhiXkdvNTDhPhLxeAxeDWNW1Tp34PxeeJEmuW3AsSeRWQEMMd:4r/aJcuvt0hhPhleMeDGCSPxeeWmHxvW |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c73338cc783e694c |
|
VISUAL
aHash
|
006660307078b690 |
|
VISUAL
dHash
|
4ccccac3e5e46431 |
|
VISUAL
wHash
|
a0666630787ebf98 |
|
VISUAL
colorHash
|
38206000000 |
|
VISUAL
cropResistant
|
85858a88da9a78fa,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 155 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)