Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1C055157AEC0C5A09707675CDE3DC0D8FE995F357E72218E696C5CF31818A818B82A97C |
|
CONTENT
ssdeep
|
3072:f7fS8chNQDu0q7hNQlu01hNQ5u0dqfSXS:f7fS8GGSC |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
f3311e4e4a1b116f |
|
VISUAL
aHash
|
00c7c7eff9ff81db |
|
VISUAL
dHash
|
191f9f9f43db2333 |
|
VISUAL
wHash
|
00c3c3c3e9fd81db |
|
VISUAL
colorHash
|
06000008058 |
|
VISUAL
cropResistant
|
191f9f9f43cb2333,44c126a25aa9d294,0418597939795804,39c5c5d4d4cdcb3b,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.