
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 9 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 218 | Medium-risk: admin panels, config files | +60 | |
| Burst: 41 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 128 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 3 | High-risk paths: shells, RCE vectors, exploits | +75 | |
| Danger medium hits: 109 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Burst: 57 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 106 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 6 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Burst: 40 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 135 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 172.161.55.226 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Implement limit_req_zone in nginx. Deploy CDN with DDoS protection. Configure SYN cookies and connection tracking to throttle 172.161.55.226.
Block scanning from 172.161.55.226: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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.
172.161.55.226 has been assigned a threat score of 280/100 (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:
Threat intelligence analysis has linked 172.161.55.226 to malicious activity originating from Zurich, Switzerland, operating on the network of Microsoft. The address has been under observation since its initial detection. The address has been active for 1 days in our monitoring system, producing 3 flagged requests at a rate of ~3/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 combination of 3 distinct attack vectors indicates a sophisticated, multi-pronged threat actor deploying automated tools that probe multiple attack surfaces simultaneously. Switzerland currently accounts for 102 blocked IPs in our database, making it a significant source of malicious traffic. With a threat score of 280/100, 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.
Insider threats — whether malicious or negligent — account for a significant percentage of data breaches. Behavioral analytics detecting unusual access patterns, data downloads, and privilege escalation help identify insider risks before damage occurs.