Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T10A042FB8271C3E2D685B96E4F725FF58132C6151BD1AD2EC92BC667026C7CE4F827884 |
|
CONTENT
ssdeep
|
1536:aHCCCCSrOCCCX029v75CCCC2aCCCCFCCCC0H2CCCCTCCCCZCCCCmCCCCrCCCCfCb:V+Ho |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
e3171c4917174b57 |
|
VISUAL
aHash
|
00e3e7e7e7f9ffff |
|
VISUAL
dHash
|
f10b4e4e0b036c3b |
|
VISUAL
wHash
|
00818383e3f9fb9f |
|
VISUAL
colorHash
|
06000000030 |
|
VISUAL
cropResistant
|
8080a2e0c080a280,1b4f4f4e0b036c3b,69e9e0e906b0e180 |
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 205 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)