Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16B1412EDAD1B267D004AEAF8D62271027D99DE444F61EE27C3E38B269767D0CDD93018 |
|
CONTENT
ssdeep
|
3072:9DlSrGjmtgbwwwcHHODlSrGjmtg7DlSrGjmtg5Rl:2AHuRl |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
92136c6dfc056d96 |
|
VISUAL
aHash
|
000c2c2c0c003cfc |
|
VISUAL
dHash
|
dc69c9c9c9c2dc39 |
|
VISUAL
wHash
|
060c7e6e0e007eff |
|
VISUAL
colorHash
|
3920a010000 |
|
VISUAL
cropResistant
|
ccd4d8d0b2baaeb2,a001494931390990,dc69c9c9c9c2dc39 |
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 10 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)