Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D3B2FAED3E1C42D5CD3363C9BF923D44750B627A84D98664D29D8EAD88D0F688DA1BC3 |
|
CONTENT
ssdeep
|
384:OLwAyRYPjcVpvJoGzSGoNqO0Vx8xmrL9sEBRiDhijySGNStGRB:aQYPInBoGmBuP2NStGRB |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
cccc3333cccccc33 |
|
VISUAL
aHash
|
0000181818180000 |
|
VISUAL
dHash
|
114db2b232320820 |
|
VISUAL
wHash
|
c3c399d9fc988187 |
|
VISUAL
colorHash
|
38400038000 |
|
VISUAL
cropResistant
|
5352ba52522a4dcd,114db2b232320820 |
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 132 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)