Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T14355037AE80D5A09707775CDE3DC0D8FE995F357E32218E696C5DF31818A818B82A87C |
|
CONTENT
ssdeep
|
3072:54fuQXhNSPGEqshNSBGE3hNS5GEmsWJXw:54fuQP2wg |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3311e4e4e1e407b |
|
VISUAL
aHash
|
00c7c3e7f9ff81db |
|
VISUAL
dHash
|
291f9e8f43cb2733 |
|
VISUAL
wHash
|
00c3c3e3e9fd819b |
|
VISUAL
colorHash
|
06000018018 |
|
VISUAL
cropResistant
|
291f9e8f43cb2333,cac2ccc4a4a4c418,0418597939795804,2d6f676e7676c38f,a39268c9587ca6a6 |
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 81 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)