Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BC93C7B051121E7FA14B83B1A690EB5B71D87B5DDB43924993FE03A63BE9CC1DC26E10 |
|
CONTENT
ssdeep
|
1536:WpKA9zeMZBcXq8McWP1eLHs5M/Z7MVpp1V1Nizn3bL1A1uhonE9sUpEhEqzIRSiD:W83Gbizn3bL1A1uhonE9sUpEhEqzIRSK |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
8d568d76213770ad |
|
VISUAL
aHash
|
063c180000001b1b |
|
VISUAL
dHash
|
cc71f0ccccc4b3b3 |
|
VISUAL
wHash
|
7e7e7e662400033f |
|
VISUAL
colorHash
|
38000000c00 |
|
VISUAL
cropResistant
|
0020ddcccc990400,cc71f0ccccc4b3b3 |
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 49 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)