Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C7E229B4A230E335B1C24BE8DA6425687A5FE1DCD7C695B0E388AF11B0D6CE9D5160CB |
|
CONTENT
ssdeep
|
768:Y7bPhOJeguHOhhPhleMeDGCSPxeeWmHPtW:uGpxFW4W |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c2c6379e4c3f6868 |
|
VISUAL
aHash
|
f076707070762660 |
|
VISUAL
dHash
|
44cc82a1a38cccc1 |
|
VISUAL
wHash
|
f076f67070762e60 |
|
VISUAL
colorHash
|
38000e00008 |
|
VISUAL
cropResistant
|
383a664ce6e2e0f1,58d8b4b260c1c180,0c00e099c8f0f898,44cc82a1a38cccc1 |
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 76 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)