Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C35195722100192A5A238AB4FAD2F784D279C74EC5A78955F3CC42EF2BD6DB0C52F324 |
|
CONTENT
ssdeep
|
48:TpJZz3z2Zzltrte4In7kd0WwY8iLh7wunNfdmdEuQ:TpV46YdqY8uh71rmdu |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc3333cccc33cccc |
|
VISUAL
aHash
|
0018181818180000 |
|
VISUAL
dHash
|
30303030b2b20c30 |
|
VISUAL
wHash
|
d8bcbcbc3c180000 |
|
VISUAL
colorHash
|
38c00018000 |
|
VISUAL
cropResistant
|
f0f0f0ecece0f0e0,30303030b2b20c30 |
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 12 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)