Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15C535F30A844DD2702DF99C8A2325B6561F98345C61712ECFEB5C3F96BAEC2CCA77254 |
|
CONTENT
ssdeep
|
1536:9uEsIxLIx47DN47HMEIX5KrbNEIOe87078zy:9uET7DN47HMEM0bNEIOp7078zy |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92e06cbe6d2e926c |
|
VISUAL
aHash
|
016e6e6e6e0e0000 |
|
VISUAL
dHash
|
739cccccccccbd10 |
|
VISUAL
wHash
|
016e7e7e7e0f0f00 |
|
VISUAL
colorHash
|
31007000000 |
|
VISUAL
cropResistant
|
82100c32320c1082,739cccccccccbd10 |
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 140 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.