Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T181B32AB47100B5271AB783A370EE47077279531ED80F8D60B3A8EA9967EDC56B523AD0 |
|
CONTENT
ssdeep
|
1536:Ebiz83jlUuRNka2wblHbJLwLIz9GguGOjjRnY:GisrX2wd9W/guGO+ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
946d99b696696694 |
|
VISUAL
aHash
|
020000640e061e1e |
|
VISUAL
dHash
|
9431d3ccdcdcd83c |
|
VISUAL
wHash
|
0e18087e7e7e1e1e |
|
VISUAL
colorHash
|
30001008041 |
|
VISUAL
cropResistant
|
91990fc0e81ab99e,666518fcb1a6b286,928b0b4261189a9e,9b8923ccf41a9998,549a9d999b9b9993,9431d3ccdcdcd83c |
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 200 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.