Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14171DD303154A57B4BA71BC6A2E0AA9E78D3A71FDE13989081FB83ED07C1FE5DD10146 |
|
CONTENT
ssdeep
|
48:T7yjCQuB7gtnvXlqXoXoqXKl0KohHZ49FyGfFizcWzy9MEi:T2ONqN+l65Z8tfyc8yOR |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc3333cc66339933 |
|
VISUAL
aHash
|
0018181818181000 |
|
VISUAL
dHash
|
0430323232323008 |
|
VISUAL
wHash
|
203c3c3c3c3c1800 |
|
VISUAL
colorHash
|
38001000007 |
|
VISUAL
cropResistant
|
0430323232323008 |
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 304 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)