
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 47.96.157.127 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
IP 47.96.157.127 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 80 | HTTP | Low | HTTP web server — standard web traffic |
| 3306 | MySQL | High | MySQL database — should never be exposed to the internet |
⚠️ Network scanning reveals 1 dangerous service exposed on 47.96.157.127. These services should not be publicly accessible without strict firewall rules.
| CVE ID | Link |
|---|---|
| CVE-2020-14814 | NVD → |
| CVE-2023-0286 | NVD → |
| CVE-2020-7070 | NVD → |
| CVE-2022-21589 | NVD → |
| CVE-2019-11039 | NVD → |
| CVE-2009-0796 | NVD → |
| CVE-2020-2752 | NVD → |
| CVE-2019-0190 | NVD → |
| CVE-2021-23841 | NVD → |
| CVE-2022-21608 | NVD → |
| CVE-2022-21595 | NVD → |
| CVE-2023-0466 | NVD → |
| CVE-2025-53020 | NVD → |
| CVE-2022-28615 | NVD → |
| CVE-2023-22026 | NVD → |
| CVE-2019-2738 | NVD → |
| CVE-2020-7064 | NVD → |
| CVE-2025-65082 | NVD → |
| CVE-2013-0942 | NVD → |
| CVE-2020-7066 | NVD → |
| CVE-2019-11041 | NVD → |
| CVE-2023-4807 | NVD → |
| CVE-2021-2146 | NVD → |
| CVE-2021-3712 | NVD → |
| CVE-2020-13938 | NVD → |
🔴 Security scanning identified 287 vulnerability entries on this host. This volume strongly suggests severely outdated software. Consult NVD advisories for details.
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
This IP was checked against major DNS-based blacklists used by mail servers and firewalls worldwide.
Checked: Spamhaus, SpamCop, Barracuda, SORBS, CBL, UCEProtect. Results may change over time.
47.96.157.127 has been assigned a threat score of 75/100 (High). This score indicates high threat severity. The IP has shown clear patterns of malicious behavior that warrant immediate defensive measures.
The following attack categories were identified:
IP address 47.96.157.127 has been traced to Hangzhou, China, operating on the network of Hangzhou Alibaba Advertising Co. Our threat detection systems have flagged this address based on observed malicious behavior patterns. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Two attack patterns were identified (User-Agent Anomaly and Path Enumeration), suggesting a semi-automated campaign that targets multiple vulnerabilities. Our records show 123 malicious IPs originating from China, positioning it as a significant contributor to global threat activity. The score of 75/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Analyzing User-Agent strings reveals automated tools masquerading as legitimate browsers. Inconsistencies between claimed browser capabilities and actual behavior, impossible version combinations, and known scanner signatures help identify malicious clients.
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.