Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DC55047AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
1536:++rSgfQTWwUoQXhNC8eqkfWKwPFwqGutEqshNC8eqkfWKwFPw+cutEQiJnP6Rrg7:FjfVoQXhNSPGEqshNSBGEthNS5GEl6XN |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
eb3416cb96136b34 |
|
VISUAL
aHash
|
000000fffff9ffff |
|
VISUAL
dHash
|
2907860e2b2b2f0c |
|
VISUAL
wHash
|
00000081fff9ffff |
|
VISUAL
colorHash
|
06601010000 |
|
VISUAL
cropResistant
|
56282b2b2b2c0d0c,fa3905068697868e |
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 50 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)