IP Threat Report
172.202.28.4
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 14 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 41 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst: 18 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 52 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 20 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 17 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 5 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 35 | Medium-risk: admin panels, config files | +60 | |
| Burst: 35 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 51 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 9 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Burst: 14 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 17 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 19 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 21 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 172.202.28.4 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
🔎 Directory Scan Defense
IP 172.202.28.4 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
🌊 Traffic Flood Defense
IP 172.202.28.4 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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
172.202.28.4 has been assigned a threat score of 255/100 (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
Network traffic from 172.202.28.4, located in Des Moines, United States, operating on the network of Microsoft, has been classified as malicious by our automated threat scoring engine. Over a period of 1 days, this IP generated 28 malicious requests, averaging approximately 28 requests per day. Classified as a hosting IP, this address likely runs on a rented server or cloud instance. Attackers prefer datacenter IPs for their high bandwidth and disposable nature. The dual attack vectors of Path Enumeration combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. Our records show 101 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. A score of 255/100 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.
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XSS attacks inject malicious scripts into web pages viewed by other users. Reflected XSS uses crafted URLs, while stored XSS persists in databases. Both types can steal session cookies, redirect users, or deface websites.
💡 Machine Learning in Threat Detection
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.