Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1984150A2AC24263BC217CBC4E9E6DE14209F818EED0A115441B446DEEFEDF84CD19CA2 |
|
CONTENT
ssdeep
|
48:AC9Lc4zf89GqlUfnN85jt7JlMyUfpK+a9WRBFJRQwHfCzPA:AVs892f+5jt9lMvfcH9WnazPA |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc7333cc66319966 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
0020323232321000 |
|
VISUAL
wHash
|
0c1c3c3c3c3c3830 |
|
VISUAL
colorHash
|
38000000e00 |
|
VISUAL
cropResistant
|
0020323232321000 |
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 36 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)