Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1D1D2B5B09348493F51C7C6F8E63AAF166328C380D7478A95E3F8876EBEC5C59DC5A184 |
|
CONTENT
ssdeep
|
384:xngFH5U+2fVY4VnD8tYMK731rq1IeH53+NfVY4VnD8t4Mq731rqi:xAH5h2j8uM21roPH5uNj8OMW1rl |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed4592167d52456d |
|
VISUAL
aHash
|
bcfff3f1f1fbffff |
|
VISUAL
dHash
|
74c3c6e342462800 |
|
VISUAL
wHash
|
0061717170700000 |
|
VISUAL
colorHash
|
00007000000 |
|
VISUAL
cropResistant
|
a1848e542ba4e4c4,69e99696b1b19196,4982b6921bdecc11,74c3c6e342462800 |
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 245 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.