Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T15555037AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:zfGQXhNSPGEqshNSBGE3hNS5GEh50SwyuJXS:zfGQPY50x5i |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3331e4e4e1c6a61 |
|
VISUAL
aHash
|
00c7c3e7f9fdffff |
|
VISUAL
dHash
|
291f9e8f434be051 |
|
VISUAL
wHash
|
0083c1c1a1f9ffdd |
|
VISUAL
colorHash
|
06000018018 |
|
VISUAL
cropResistant
|
391f9e8f434be051,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 48 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.
Pages with identical visual appearance (based on perceptual hash)