
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA changed for same IP | Multiple User-Agents — bot rotation technique | +25 | |
| Danger medium hits: 4 | Medium-risk: admin panels, config files | +40 | |
| 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: 14 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 14 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Burst: 18 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 21 req / 10s | Abnormally fast request rate — automated scanning | +35 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 34.123.3.200: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Block scanning from 34.123.3.200: 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 34.123.3.200.
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 |
| CVE ID | Link |
|---|---|
| CVE-2026-35414 | NVD → |
| CVE-2025-26465 | NVD → |
| CVE-2026-35387 | NVD → |
| CVE-2023-51767 | NVD → |
| CVE-2025-26466 | NVD → |
| CVE-2026-35388 | NVD → |
| CVE-2026-35385 | NVD → |
| CVE-2008-3844 | NVD → |
| CVE-2026-35386 | NVD → |
| CVE-2007-2768 | NVD → |
| CVE-2025-32728 | NVD → |
🔴 This host has 11 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 This volume strongly suggests severely outdated software.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.
34.123.3.200 has been assigned a threat score of 180/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
34.123.3.200 is registered in Council Bluffs, United States, operating on the network of Google LLC. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. Our sensors captured 2 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~2 requests per day. This address belongs to a datacenter or cloud hosting provider. Hosting IPs are frequently leveraged by threat actors who rent cheap VPS instances specifically for conducting attacks. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. With 142 flagged addresses, United States represents a significant presence in our threat database. A score of 180/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Examining HTTP headers beyond User-Agent reveals attack tools and automated scripts. Missing standard headers, unusual ordering, non-standard values, and inconsistencies with claimed client identity all serve as reliable detection signals.
Modern deception technology deploys fake credentials, decoy files, and breadcrumbs throughout production environments. When attackers interact with these deceptions, high-fidelity alerts trigger with virtually zero false positives.