Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11FF1941E9DCC5C032227B6ACFE2983E9F283D187C6385901B2D85F7C46C7F599865B1A |
|
CONTENT
ssdeep
|
96:xfwq5oS8oJwo4oIoHoNnolQeWIlI7c7qWkySCtcxDHOM5cvNGpAYwAY05RyjoPSP:CUojoJwo4oIoHoNnoKrIlJUH5Fco6eoV |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b2e40f9a354958bd |
|
VISUAL
aHash
|
e7f7c3c3c78d3d00 |
|
VISUAL
dHash
|
4d0e978f2d396b6b |
|
VISUAL
wHash
|
20f7c7c3c7cd3d00 |
|
VISUAL
colorHash
|
07e00000002 |
|
VISUAL
cropResistant
|
6e0e978fad39696b,444c0e4e9797858f,0110322667d75f59,696b6b6b6b6b6b00 |
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 5 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)