Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11055037AEC0D5A09707675CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
1536:37rSqfQ7QXhNC8eqkfWKwPFwqGutEqshNC8eqkfWKwFPw+cutEQiJnP6Rr+S2ADA:fhfsQXhNSPGEqshNSBGEDhNS5GEf86XS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3331e4a49117b4b |
|
VISUAL
aHash
|
00c7c3e7f9fdffff |
|
VISUAL
dHash
|
190f8f9f434be011 |
|
VISUAL
wHash
|
00c3c1c1a1f9ffd9 |
|
VISUAL
colorHash
|
06000000418 |
|
VISUAL
cropResistant
|
190f8f9f434be031,c46564646ca85356,0418597939795804,c3d3c3c7c3e7cfcf |
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 48 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)