Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BF53AEA0E1244A739CB3F2D5D0613F493EDBF20BE106E791BBE44A955FC7CA979064A0 |
|
CONTENT
ssdeep
|
1536:taj4WouFzYGR2yIBZK1QZhBPI1s4yhBPI1MthBPI1MxhBPI12xZzZzZzZzZQTh2l:ta0WouFzYGR2yIBZK1QZhBPI1s4yhBPv |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cb4b9696d6c2c84b |
|
VISUAL
aHash
|
ff0999f9f9fffbff |
|
VISUAL
dHash
|
5973332375344b01 |
|
VISUAL
wHash
|
bd08199905df01ff |
|
VISUAL
colorHash
|
070000001c0 |
|
VISUAL
cropResistant
|
5973332375344b01,35162e6b29292534 |
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 43 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)