Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T11F55037AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:TGfjQXhNSPGEqshNSBGE3hNS5GEtRV8JXw:TGfjQPEWg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3331e4e4e1c4279 |
|
VISUAL
aHash
|
00c7c3e7f9ff83fb |
|
VISUAL
dHash
|
291f9e8f434b3717 |
|
VISUAL
wHash
|
00c3c3e3e1fd81db |
|
VISUAL
colorHash
|
06000018018 |
|
VISUAL
cropResistant
|
291f9e8f434b3717,cacaccc4a4a4c458,0418597939795804,2d6f6f6e56768b8f,896d0d1931294b0f |
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 50 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.