Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T104A2CC380E2AAAF709C382F1A5BA075F71D1ADA7CA87460436F8874D5FDBDC1CD4614A |
|
CONTENT
ssdeep
|
384:mC8/hBTq0d0OP2wysSKpJR3dNIAXej0zQA2BgR0a:mC8/hBTq0d0OP2wysSKXR3deAOj0sBgv |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
9908666673f1d999 |
|
VISUAL
aHash
|
0018183c3c3c1800 |
|
VISUAL
dHash
|
4db3b232b2b2b2cc |
|
VISUAL
wHash
|
00183c7efe3c7f03 |
|
VISUAL
colorHash
|
07007000000 |
|
VISUAL
cropResistant
|
c83d375b631d59ea,4db3b232b2b2b2cc,afc9999f34656fc9,7255d99bcb52143c |
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 944 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.