Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14EC30AA1E6F8517B904383CCD169B17031F761BFFBC0921062FA4B685666CCA7C1BD6A |
|
CONTENT
ssdeep
|
1536:78h3wddEarQUzRo2hpHFm/2CzoEzfE/9qWTY8W7m3nqbfiASmDbmJXe0IUv:uLDbpM |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
edcd129207ed0e6c |
|
VISUAL
aHash
|
fffbfbfbffff8100 |
|
VISUAL
dHash
|
c8323332362a0b83 |
|
VISUAL
wHash
|
7f8b91d3f3fb0000 |
|
VISUAL
colorHash
|
0e0000002c0 |
|
VISUAL
cropResistant
|
c41a333332372b0b,d40b2bd4a2134da2,e47a3d0e87c7c1d0,996c76360b0349c8,3130d3d393b22c2d,0b0304738b8b2b03 |
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 827 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)