Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1F1330124310145FF96A7C9E0F060BF1962ABF34EC66FCD99A3ED11A12FCBCB1A552560 |
|
CONTENT
ssdeep
|
768:hYQ5b1b55bNbNb4bBYdd5OzhK7KVRrkV8zaCwTHywEVRvHPvEnL7iMh:X5Z15xhMl+5OdKVpCwzq2b |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
842a3b3acbeaaa3a |
|
VISUAL
aHash
|
0102067636160662 |
|
VISUAL
dHash
|
131c94c4e4e40cc2 |
|
VISUAL
wHash
|
c106067e7e3e067e |
|
VISUAL
colorHash
|
38042001000 |
|
VISUAL
cropResistant
|
131c94c4e4e40cc2 |
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 57 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)