Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T114246129D3340334CAAE0FDCC5F55816254900DF293066D8EA1BD6B7FEB1DE92472A9E |
|
CONTENT
ssdeep
|
3072:pi1AjlPEEv9oS92uSCn9CxdCcv6Qm6rbDP/Uj/Ai8mnlRb+7926SUiSBnBuHKS97:pk65NEVzZc7 |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ed41923ebd61c649 |
|
VISUAL
aHash
|
01007000000000ff |
|
VISUAL
dHash
|
3be0c21632212b04 |
|
VISUAL
wHash
|
9f7078420200ffff |
|
VISUAL
colorHash
|
010000001c0 |
|
VISUAL
cropResistant
|
bab2ac8adac42c29,5454cb119b4948a4,3425e6ce25a5c9cb,0000000000000000,3384e1d6323221cb |
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 348 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.