Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T101F2E7356605556B43BB99C1F2617F1F75D3F30F80168606ABBC918A2FC7CB6BB201A2 |
|
CONTENT
ssdeep
|
384:3CCygRFbFzFfFwFNCFOxFlFA2F3MmpVaR/:33hptwNGODfAi3MLJ |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b333338ccccccc33 |
|
VISUAL
aHash
|
e3c3c3ffffffe7ef |
|
VISUAL
dHash
|
cc4e4e041c0c4d0c |
|
VISUAL
wHash
|
00c3c3e3e7c3c3c7 |
|
VISUAL
colorHash
|
070010100c0 |
|
VISUAL
cropResistant
|
cc4e4e041c0c4d0c,c6c6b0f0f6d9494c,71b8bc9cbcecfad8 |
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 22 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)