Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AC3375735451353B432757C9F123371EF1A3930ECB8B48A8B3B987924BE3DA9991981E |
|
CONTENT
ssdeep
|
1536:v3WFvhtQI06534+Pf17kw2eQOC+r7K+0FOfr3Ku9cMV83IbLQT1Pif/BCjOEX4G0:vMv++bW/3YT |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a152af2dd2ada952 |
|
VISUAL
aHash
|
000040444403033f |
|
VISUAL
dHash
|
440c8c8c8c0fc76b |
|
VISUAL
wHash
|
e70666766607033f |
|
VISUAL
colorHash
|
38040006000 |
|
VISUAL
cropResistant
|
804b726971710c14,440c8c8c8c0fc76b,016928174d30b10d |
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 822 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)