IP Threat Report
129.121.35.57
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: Go-http-client | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 14 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 6 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 strong hits: 6 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 |
Observed Activity
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Timeline
Network Provider
Recommendations
Actions taken & recommended
- IP 129.121.35.57 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 User-Agent Anomaly Defense
IP 129.121.35.57 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
🌊 Traffic Flood Defense
IP 129.121.35.57 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
🔎 Path Enumeration Protection
Block scanning from 129.121.35.57: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Open Ports & Services
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 |
| 443 | HTTPS | Low | HTTPS web server — encrypted web traffic |
| CVE ID | Link |
|---|---|
| CVE-2025-23419 | NVD → |
| CVE-2023-44487 | NVD → |
| CVE-2021-3618 | NVD → |
| CVE-2021-23017 | NVD → |
🔴 Security scanning identified 4 vulnerability entries on this host. Multiple vulnerabilities suggest gaps in patch management. Consult NVD advisories for details.
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
Blacklist Status (DNSBL)
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.
Threat Analysis
129.121.35.57 has been assigned a threat score of 220/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
The following attack categories were identified:
📊 Threat Analysis
Our monitoring infrastructure has identified 129.121.35.57, geolocated to Vinhedo, Brazil, operating on the network of Oracle Corporation, as a source of suspicious network activity. The address has been active for 1 days in our monitoring system, producing 2 flagged requests at a rate of ~2/day. The address is classified as residential, meaning it likely belongs to an end-user ISP connection. Malicious activity from residential IPs typically indicates device compromise or botnet membership. The combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. Our records show 101 malicious IPs originating from Brazil, positioning it as a significant contributor to global threat activity. A score of 220/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
Related Threats
Security Intelligence
💡 User-Agent Analysis Techniques
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.
💡 Behavioral Analysis vs Signature Detection
Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.