
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Danger medium hits: 72 | Medium-risk: admin panels, config files | +60 | |
| Burst: 24 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 71 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 9 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 200 | Medium-risk: admin panels, config files | +60 | |
| Burst: 80 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 6 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 127 | Medium-risk: admin panels, config files | +60 | |
| Burst: 22 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 76 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 12 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 300 | Medium-risk: admin panels, config files | +60 | |
| Burst: 25 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 90 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 88 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 83 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 87 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 82 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 84 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.
IP 52.179.214.126 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
IP 52.179.214.126 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
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.
52.179.214.126 has been assigned a threat score of 245/100 (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 intelligence analysis has linked 52.179.214.126 to malicious activity originating from Boydton, United States, operating on the network of Microsoft Corporation. The address has been under observation since its initial detection. Our sensors captured 15 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~15 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 User-Agent Anomaly combined with Request Flooding indicate a coordinated assault rather than opportunistic scanning. United States currently accounts for 101 blocked IPs in our database, making it a significant source of malicious traffic. A score of 245/100 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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
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.