Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D2718C20B03C9E37818B95D9A5E29B4B32D6C305CF43174587F5C7AE2BD3C94DE485A6 |
|
CONTENT
ssdeep
|
96:T5Q8kMkJDa4K+ETzFqKyW2QF1qsAgOI9DcqgbltSw:83JD/MTqVH3bltSw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc3333cccc3333cc |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
0008103232300c00 |
|
VISUAL
wHash
|
0000181818180000 |
|
VISUAL
colorHash
|
380000001c0 |
|
VISUAL
cropResistant
|
0008103232300c00 |
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 4 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)