Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T17F55037AE80D5A09707675CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
1536:z3rSEf9YQXhNC8eqkfWKwPFwqGutEqshNC8eqkfWKwFPw+cutEQiJnP6Rr+S2AD+:3LfiQXhNSPGEqshNSBGE3hNS5GET/JXw |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3311e4e4e0e546b |
|
VISUAL
aHash
|
00c7c3e7f9ffa1ff |
|
VISUAL
dHash
|
291f9e8f434b4b6b |
|
VISUAL
wHash
|
00c3c3c3e1fd81fb |
|
VISUAL
colorHash
|
06000018018 |
|
VISUAL
cropResistant
|
291f9e8f435b4b6b,cac2ccc4a4a4c418,0418597939795804,2d6f676e7676c38f |
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.