Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16F833BA43E59F1661AF3439720DF24037278931B540E4D20A214FDAE75BCC9BA16BFDA |
|
CONTENT
ssdeep
|
1536:AG+mx0HKBtUFt7ftqQ0L3jn6mnOuwWlYoxxKXVU3y:A0x0HKBtUV0Lz6mnOuz3PKXVU3y |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
999966669999cc66 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
304cb2b2b2b24c30 |
|
VISUAL
wHash
|
01003c3c1c1c0000 |
|
VISUAL
colorHash
|
38000038000 |
|
VISUAL
cropResistant
|
8e8686f878d05186,304cb2b2b2b24c30 |
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 32 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)