Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16655037AEC0D5A09707675CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
1536:KEoZfANQXhNC8eqkfWKwPFwqGutEqshNC8eqkfWKwFPw+cutEQiJnP6Rr+S2ADAm:WfUQXhNSPGEqshNSBGE3hNS5GE9CVJXS |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3311a4a4e1e4d3b |
|
VISUAL
aHash
|
00c7c3e7f9ff87ff |
|
VISUAL
dHash
|
291f9e8f43430d15 |
|
VISUAL
wHash
|
00c3c3e3e1fd81db |
|
VISUAL
colorHash
|
06000010018 |
|
VISUAL
cropResistant
|
391f9e8f43430d15,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 79 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.