IP Threat Report
160.153.189.17
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| Danger medium hits: 10 | Medium-risk: admin panels, config files | +60 | |
| Burst: 6 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 14 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Danger strong hits: 7 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 7 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 6 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger strong hits: 14 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 11 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 10 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 13 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 12 req / 2s | 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 160.153.189.17 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
🤖 Bot Detection
Address UA spoofing from 160.153.189.17: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
🌊 Flood / DDoS Mitigation
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 160.153.189.17.
🔎 Path Enumeration Protection
Block scanning from 160.153.189.17: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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
160.153.189.17 has been assigned a threat score of 220/100 (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
Our monitoring infrastructure has identified 160.153.189.17, geolocated to Tempe, United States, operating on the network of GoDaddy.com, LLC, as a source of suspicious network activity. The address has been active for 8 days in our monitoring system, producing 22 flagged requests at a rate of ~2.8/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. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. United States currently accounts for 105 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 220/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
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💡 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.
💡 Emerging Threats from AI-Powered Attacks
Artificial intelligence enables more convincing phishing content, faster vulnerability discovery, and adaptive attack strategies that learn from defensive responses. AI-generated social engineering and automated exploit development represent growing threats.