
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Burst 6/2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 10 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 10 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 5 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 6 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Probe 302→404 | Behavioral anomaly detected by automated analysis | +20 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 |
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 51.68.236.59: 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 51.68.236.59.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 22 | SSH | Low | Secure Shell — common brute force target for remote access |
| 80 | HTTP | Low | HTTP web server — standard web traffic |
| CVE ID | Link |
|---|---|
| CVE-2025-26465 | NVD → |
| CVE-2025-66200 | NVD → |
| CVE-2024-42516 | NVD → |
| CVE-2025-23048 | NVD → |
| CVE-2012-4001 | NVD → |
| CVE-2009-2299 | NVD → |
| CVE-2012-3526 | NVD → |
| CVE-2013-0941 | NVD → |
| CVE-2013-0942 | NVD → |
| CVE-2011-2688 | NVD → |
| CVE-2013-4365 | NVD → |
| CVE-2025-58098 | NVD → |
| CVE-2025-32728 | NVD → |
| CVE-2009-0796 | NVD → |
| CVE-2007-2768 | NVD → |
| CVE-2011-1176 | NVD → |
| CVE-2016-20012 | NVD → |
| CVE-2025-59775 | NVD → |
| CVE-2025-49812 | NVD → |
| CVE-2013-2765 | NVD → |
| CVE-2021-36368 | NVD → |
| CVE-2025-65082 | NVD → |
| CVE-2024-47252 | NVD → |
| CVE-2023-51767 | NVD → |
| CVE-2025-53020 | NVD → |
🔴 This host has 37 known CVEs associated with its exposed services. This volume strongly suggests severely outdated software. Review each CVE in the NVD database.
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.
51.68.236.59 has been assigned a threat score of 70/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
The following attack categories were identified:
Network traffic from 51.68.236.59, located in Roubaix, France, operating on the network of OVH SAS, has been classified as malicious by our automated threat scoring engine. The address has been active for 81 days in our monitoring system, producing 939 flagged requests at a rate of ~11.6/day. Operating from datacenter infrastructure, this IP is typical of addresses used in organized attack operations. Cloud and VPS providers are commonly exploited as launching platforms for automated scanning. Two attack patterns were identified (Path Enumeration and Request Flooding), suggesting a semi-automated campaign that targets multiple vulnerabilities. France currently accounts for 125 blocked IPs in our database, making it a significant source of malicious traffic. The score of 70/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
This IP belongs to a hosting or data center provider. Malicious traffic from hosting infrastructure often originates from compromised VPS instances, rented servers used for scanning campaigns, or abused free-tier cloud accounts. Hosting providers typically respond to abuse reports within 24-72 hours.
Distributed denial of service attacks overwhelm infrastructure with traffic volume. Effective mitigation combines always-on traffic scrubbing, anycast network distribution, rate limiting, and the ability to quickly scale absorption capacity during attacks.
Internet of Things devices are prime targets for botnet recruitment due to weak default credentials, infrequent updates, and always-on connectivity. Compromised IoT devices generate persistent scanning and attack traffic without their owners knowledge.