Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1DFF32DB43695F4920AB746A3806F0002F3385D3B140D5D60A395ECEE757999EA0F7FEA |
|
CONTENT
ssdeep
|
1536:fuC6/5TGdiGoha6Ih6PgRs5Vx2t8qL123OFoyCRFX6C2KWT9sPaUduJodvSbv1h8:fcGohSQ4RgV8W6KOoN |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9352d6f5751c0b07 |
|
VISUAL
aHash
|
e6fc3d89e3ffffe7 |
|
VISUAL
dHash
|
0c69792bca142908 |
|
VISUAL
wHash
|
e4fc3c00c3ff00c7 |
|
VISUAL
colorHash
|
07000030000 |
|
VISUAL
cropResistant
|
0c69792bca142908 |
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 10 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)