Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D2B34032B150D52A4DC744DCF2B1AB08155EE305FF3284A965F4A2BFA3DADE8A9113DC |
|
CONTENT
ssdeep
|
768:tOn5sHrn5sHpeJk1kL5T9IG6I/m1TYrSljvRCR4dqXiJ/X41akpB7d0QulREOn5i:t0189FrCzgMj2BW189FrCzgMj2v |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a9e969f4f0138716 |
|
VISUAL
aHash
|
fbd119dfdfff0000 |
|
VISUAL
dHash
|
b3337b9334403298 |
|
VISUAL
wHash
|
ffc101cfd7ff0000 |
|
VISUAL
colorHash
|
071c0000000 |
|
VISUAL
cropResistant
|
b3337b9334403298,000c3b06c15881c9,112327861431d9b3 |
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 1120 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)