Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T18F327331A6A0012F223386DAF655EB1CA1CBDB4BCE178C54F1BCA29397C6C858E58961 |
|
CONTENT
ssdeep
|
192:gPX82XYjH6YjRYjPqhSIQX3bYf2PB8XazIgmItG7RgcMJu:6X82XYjaYjRYjPM/iLZmK/mIcLMw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8cffa280dff78088 |
|
VISUAL
aHash
|
ff00009018180000 |
|
VISUAL
dHash
|
e548707032b28ce4 |
|
VISUAL
wHash
|
ffa298981818003f |
|
VISUAL
colorHash
|
06c00000000 |
|
VISUAL
cropResistant
|
0000446969690628,e548707032b28ce4 |
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 20 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)