
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Burst: 6 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block scanning from 107.172.177.71: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 107.172.177.71.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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 |
| 8000 | Unknown | Low | Service on port 8000 |
| 8080 | HTTP-Alt | Low | HTTP alternative port — often used for admin panels or proxies |
| 8800 | Unknown | Low | Service on port 8800 |
| 21242 | Unknown | Low | Service on port 21242 |
| CVE ID | Link |
|---|---|
| CVE-2026-33515 | NVD → |
| CVE-2021-31806 | NVD → |
| CVE-2018-19131 | NVD → |
| CVE-2020-15049 | NVD → |
| CVE-2023-46728 | NVD → |
| CVE-2019-12522 | NVD → |
| CVE-2021-28116 | NVD → |
| CVE-2020-15810 | NVD → |
| CVE-2020-11945 | NVD → |
| CVE-2022-41318 | NVD → |
| CVE-2020-24606 | NVD → |
| CVE-2019-12520 | NVD → |
| CVE-2019-12519 | NVD → |
| CVE-2020-8449 | NVD → |
| CVE-2019-12523 | NVD → |
| CVE-2020-25097 | NVD → |
| CVE-2018-1000024 | NVD → |
| CVE-2023-46846 | NVD → |
| CVE-2021-31807 | NVD → |
| CVE-2019-12521 | NVD → |
| CVE-2020-8517 | NVD → |
| CVE-2016-10003 | NVD → |
| CVE-2016-10002 | NVD → |
| CVE-2018-1000027 | NVD → |
| CVE-2025-59362 | NVD → |
🔴 Security scanning identified 59 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 This volume strongly suggests severely outdated software.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.
107.172.177.71 has been assigned a threat score of 140/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
IP address 107.172.177.71 has been traced to Buffalo, United States, operating on the network of HostPapa. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Our sensors captured 1 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~1 requests per day. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. Two attack patterns were identified (Path Enumeration and Request Flooding), suggesting a semi-automated campaign that targets multiple vulnerabilities. Our records show 200 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. At 140/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
Modern attacks increasingly target APIs rather than traditional web interfaces. Attackers enumerate endpoints, test for broken authentication, and exploit excessive data exposure. API attacks are harder to detect as they mimic legitimate programmatic access patterns.
Deepfake audio and video enable convincing impersonation of executives and trusted individuals. Real-time voice cloning has been used in successful fraud campaigns, adding a new dimension to social engineering that traditional security training does not address.