
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 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Foreign referer seen | Referer from unrelated external domain | +10 | |
| Danger strong hits: 20 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Burst: 26 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 26 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 30 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 39 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 39 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 37 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 35 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 40 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Burst: 52 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 52 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 46 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 44 req / 2s | 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.
Address UA spoofing from 34.46.170.196: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Block scanning from 34.46.170.196: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 34.46.170.196.
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.
34.46.170.196 has been assigned a threat score of 230/100 (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:
Network traffic from 34.46.170.196, located in Council Bluffs, United States, operating on the network of Google LLC, has been classified as malicious by our automated threat scoring engine. The address has been active for 1 days in our monitoring system, producing 68 flagged requests at a rate of ~68/day. Operating from datacenter infrastructure, this IP is typical of addresses used in organized attack operations. Cloud and VPS providers are commonly exploited as launching platforms for automated scanning. The diversity of 3 separate attack methods suggests a comprehensive attack toolkit — likely an automated scanner that tests for vulnerabilities across multiple categories. Our records show 142 malicious IPs originating from United States, positioning it as a significant contributor to global threat activity. With a threat score of 230/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly recommended.
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.
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.
Internet traffic routing through a limited number of submarine cables and exchange points creates natural chokepoints. Understanding these routing patterns helps explain geographic clustering of certain attack types and latency-based scanning behaviors.