Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1CAA2D031F112346A5533C4D0F8E95F28F887D736C3A64D14E3AD6A696FCACE05A607A8 |
|
CONTENT
ssdeep
|
384:/rgvnkNkNWNiN5NrN/Ztqm8wIAS54rO54+e54Yu54sK543IHv0v/YD5LfVz5LfVj:TgvnEEKuTZ/Hqm8w1FrR+BYxsN3IP0v8 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f54a2853275f2f0a |
|
VISUAL
aHash
|
00ff80fe66feee03 |
|
VISUAL
dHash
|
1696324ccc8a8a16 |
|
VISUAL
wHash
|
00ff806e6eee00bf |
|
VISUAL
colorHash
|
07200000206 |
|
VISUAL
cropResistant
|
1696324ccc8a8a16 |
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 912 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)