Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T19055157AEC0C5A09707675CDE3DC0D8FE995F357E72218E696C5CF31818A818B82A97C |
|
CONTENT
ssdeep
|
1536:E0rS0fBg8chNFteqTMW6wlD6xHWt0q7hNFteqTMW6wL96NVWt0FiJnP6RrAF0/VR:ZPfS8chNQDu0q7hNQlu0QhNQ5u0HLiXY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e3311e4b5b1e516a |
|
VISUAL
aHash
|
00e7c3e7f9ff81c7 |
|
VISUAL
dHash
|
39078f8f43cb272b |
|
VISUAL
wHash
|
00c3c3e3e9fd81cb |
|
VISUAL
colorHash
|
06000010018 |
|
VISUAL
cropResistant
|
190f8f9f43c3272b,0418597939795804 |
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 82 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)