Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T13E51DE734108AC1A2722B2D8CB1263CED1D3405FCED31545E2EA43AA96FCDF549DA677 |
|
CONTENT
ssdeep
|
48:TIc9BeR4cUqgEeLCRfwD4gsJnOcwwAjHp5BxAQCdJ7E7lfUix:THDeiZKWJpzfAQxfUix |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
99cc663399cccc99 |
|
VISUAL
aHash
|
0000181818000000 |
|
VISUAL
dHash
|
a24db2b2b2b14db2 |
|
VISUAL
wHash
|
bf0018bfbf1800bf |
|
VISUAL
colorHash
|
011c0000000 |
|
VISUAL
cropResistant
|
8e8f0f4d091d0d4f,a24db2b2b2b14db2 |
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 16 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)