Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1AC3384326411363B432757C9B066375EF193930ECB9B48A8B3BD87D30BE3DA59919C1A |
|
CONTENT
ssdeep
|
1536:vAWFvhtQI56534+Pf17kw2eQOC+E7K+0FOfr3Ku9cMV83IbLmCjOEX4GLyQ7CpS:vpv3+uWo3Wg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
a152af2dd2ada952 |
|
VISUAL
aHash
|
000040444403033f |
|
VISUAL
dHash
|
44008c8c8c03c76b |
|
VISUAL
wHash
|
f70066766703037f |
|
VISUAL
colorHash
|
38040006000 |
|
VISUAL
cropResistant
|
804b726971710c14,44008c8c8c03c76b,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)