Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11D222170310634662237CBD1F0A14F0D62279339C7561E5AB7E91673EFC9CE899A27A8 |
|
CONTENT
ssdeep
|
192:mNhb4gSqddQCnNZvXknP7lOyp9a9dvErEF15LfR3LfRqLfRYLfRtMKNqyTzhBeCz:wBUEw/p8dF15LfR3LfRqLfRYLfRtNtTx |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
fffd080000a2f77e |
|
VISUAL
aHash
|
0000ffff00000000 |
|
VISUAL
dHash
|
9110488000000111 |
|
VISUAL
wHash
|
19ffffff00000119 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
0000080808080000,9110488000000111 |
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 353 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)