Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T12053A672A3A9063F521B09D870702B4B31E7E34DEA179814D2EC435B6FD7CA0DC9ADA5 |
|
CONTENT
ssdeep
|
1536:GPS4AmJWuDBFEpJWUNOWGCnkm5AFUTWhWdUmDdNEkgh4MMKiPvEHxVjujIlddE+F:GtaDDo/q8REag22te |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
dc567256dc8d2323 |
|
VISUAL
aHash
|
0400183c3c180000 |
|
VISUAL
dHash
|
7c5c717270704fa0 |
|
VISUAL
wHash
|
040c3c3c3c383fff |
|
VISUAL
colorHash
|
070000001c2 |
|
VISUAL
cropResistant
|
8a8ca8a2803323c4,7c5c717270704fa0 |
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 5 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)