Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D555037AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:6zfjQXhNSPGEqshNSBGEWhNS5GEibcrXS:6zfjQPgbyi |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3731e4a4b1c6338 |
|
VISUAL
aHash
|
00c7c3e3f9fddfff |
|
VISUAL
dHash
|
391f9e8f434bb03b |
|
VISUAL
wHash
|
00c3c1c1e1f9dfcb |
|
VISUAL
colorHash
|
06000000418 |
|
VISUAL
cropResistant
|
191f9e8f434bb03b,a2ae94a8d874b4a4,0418597939795804,d3d3e7e7e6f2cbce,383c8e959c9a9ecd |
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.