Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17FC1BC7050689D3B51A7A0DAB3F59BA736E9C302CE471704D2FC97AD0BD3C94DE1A491 |
|
CONTENT
ssdeep
|
96:T+zUfodn3Z+Bh+UYZERwIAq+FbDSgUN95nCXYX1Gae1tmEpbgtIe:64AdnwGawI8FbDSXN99CXdae1tzpb5e |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9999666699996666 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
304c32b2b2320c20 |
|
VISUAL
wHash
|
0f0f1b1b18180000 |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
6c6cda6c6a807171,304c32b2b2320c20 |
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 24 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)