Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F255037AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:b6fHQXhNSPGEqshNSBGEYhNS5GEXPt0jJ3Ry1JXw:b6fHQPTaRyng |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3331e4e4e1c5169 |
|
VISUAL
aHash
|
00c7c3eff9ff81cb |
|
VISUAL
dHash
|
291d9f9b43cb1313 |
|
VISUAL
wHash
|
00c7c3e3e1fd81cb |
|
VISUAL
colorHash
|
06200010018 |
|
VISUAL
cropResistant
|
291f9f9b43cb1313,0418597939795804,23555d214d77522e |
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 81 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)