Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17C4309F4818076B6940787F8D738EB4A7247707FE70E8A4993F88B812F59C769A0D9D4 |
|
CONTENT
ssdeep
|
768:IvFvcI3S3s3tp2xmWf+ppjiDaBcCGhl8tihyghzihc:IO+XfpjiDachyAhyghzihc |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
c9b616493ca936cb |
|
VISUAL
aHash
|
ffffffd1f8f8f800 |
|
VISUAL
dHash
|
330f2c1332121212 |
|
VISUAL
wHash
|
ffe7ff80d0d0e000 |
|
VISUAL
colorHash
|
0f0000001c0 |
|
VISUAL
cropResistant
|
330f281332321212,000008b2b2320c10,32321232121212d2 |
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)