Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1B8E26530404390771583A5D2B7366F5AB7E18348DB63074892FD879E6FEAC50DC2BA79 |
|
CONTENT
ssdeep
|
384:gM4OTeNa9GK4YHXKcNk9Gs90sB8/HAG85i3/ZyPvd4Fzaf2ZQF:J4OrAe0As6sB8fAG85i3/ZKd4FzG2w |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
ec13eeec106dca13 |
|
VISUAL
aHash
|
000000000efff3fb |
|
VISUAL
dHash
|
0fd5d9dedc672727 |
|
VISUAL
wHash
|
000008023fffffff |
|
VISUAL
colorHash
|
12001000180 |
|
VISUAL
cropResistant
|
d867672327272727,d85c7226a632524c,3fd7f7d4d9de9efc,6fb0f2ca94d27070 |
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 21 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.