Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T16C55157AEC0C5A09707675CDE3DC0D8FE995F357E72218E696C5CF31818A818B82A97C |
|
CONTENT
ssdeep
|
1536:PtrSWfBg8chNFteqTMW6wlD6xHWt0q7hNFteqTMW6wL96NVWt0FiJnP6Rr/hnM+s:VNfS8chNQDu0q7hNQlu01hNQ5u0gAaXY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3311e4e4f1b116a |
|
VISUAL
aHash
|
00c7c3eff9ff81ff |
|
VISUAL
dHash
|
191f9f9f43cb3b2b |
|
VISUAL
wHash
|
00c3c3c3e9fd81dd |
|
VISUAL
colorHash
|
06000000098 |
|
VISUAL
cropResistant
|
191f9f9f434b3b2b,44c126a25aa9d294,0418597939795804,39c5c5d4d4cdcb3b |
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 82 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.