IP Threat Report
113.249.101.176
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: java | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 2 | High-risk paths: shells, RCE vectors, exploits | +50 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Burst: 9 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 26 req / 10s | Abnormally fast request rate — automated scanning | +35 |
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 113.249.101.176 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Other malicious IPs detected in the same /24 subnet — consider blocking 113.249.101.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🤖 Bot Detection
Address UA spoofing from 113.249.101.176: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
🔎 Directory Scan Defense
IP 113.249.101.176 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 113.249.101.176.
Neighbors in 113.249.101.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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
113.249.101.176 has been assigned a threat score of 200/100 (Critical). This places it in the critical threat category. Immediate blocking is strongly advised across all network perimeters.
The following attack categories were identified:
📊 Threat Analysis
113.249.101.176 is registered in Chongqing, China, operating on the network of Chongqing Telecom. This IP first appeared in our threat feeds after triggering multiple behavioral detection signatures. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. 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 194 malicious IPs originating from China, positioning it as a significant contributor to global threat activity. At 200/100, 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.
Related Threats
Security Intelligence
💡 HTTP Header Analysis for Threat Detection
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.
💡 IP Geolocation Accuracy Limitations
IP geolocation databases provide approximate locations with varying accuracy. City-level geolocation is typically 50-80% accurate, while country-level exceeds 95%. VPNs, proxies, and mobile networks further reduce reliability, making geolocation a useful but imperfect intelligence signal.