Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1BE7185E56067B833418791E5B7173B5BB2E10566C94F1A0480FDF2C90FEBE84DD1A0E9 |
|
CONTENT
ssdeep
|
48:T2HbIcmdJmcn2n5JcjEL+az8czwGK7c5dyS1VzG:TyI6c2n5J58uK7+DG |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cc997326cc999966 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
000c323230320400 |
|
VISUAL
wHash
|
30303c3c1b1b3332 |
|
VISUAL
colorHash
|
07000000180 |
|
VISUAL
cropResistant
|
000c323230320400 |
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 4 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)