Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1EC3207F8722404E1EE0397DAB92232BAA043927EDE935698D3698754B6D5CFDCC40DC6 |
|
CONTENT
ssdeep
|
192:Qo7oBZJ5I9fDMu9cuGRmKbMpBXp7sfgg8gk:QioWgsmMpBZ7eg/B |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
be1ad560c0ab2db5 |
|
VISUAL
aHash
|
ffbe00000000ffff |
|
VISUAL
dHash
|
cc7d717175550d8c |
|
VISUAL
wHash
|
ff9f01010000ffff |
|
VISUAL
colorHash
|
0fc00008000 |
|
VISUAL
cropResistant
|
cc7d717175550d8c,636ac6d6e4bcd97a,83f03ccb79f43aea,c4a28a273392a2c4,a282d04b5351aa92,0b0b0b8ba180a0a0,bc3ebaf17134d6b6 |
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 487 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)
Found 1 other scan for this domain