
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA suspicious (short/empty) | Behavioral anomaly detected by automated analysis | +15 | |
| Danger strong hits: 50 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 420 | Medium-risk: admin panels, config files | +60 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Burst: 41 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 138 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 32 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 105 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 67 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| Danger medium hits: 630 | Medium-risk: admin panels, config files | +60 | |
| Burst: 38 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 129 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Danger strong hits: 34 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Burst: 45 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 162 req / 10s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 40 req / 2s | Abnormally fast request rate — automated scanning | +35 | |
| Burst: 142 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 158.158.109.20 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Block scanning from 158.158.109.20: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
IP 158.158.109.20 is generating excessive traffic. Limit connections per source IP. Enable geographic blocking if traffic from this region is unexpected.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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.
158.158.109.20 has been assigned a threat score of 280/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
IP address 158.158.109.20 has been traced to Madrid, Spain, operating on the network of Microsoft Corporation. Our threat detection systems have flagged this address based on observed malicious behavior patterns. Our sensors captured 5 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~5 requests per 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. With 3 different attack patterns detected, this IP exhibits behavior characteristic of advanced automated scanning frameworks. Spain currently accounts for 114 blocked IPs in our database, making it a significant source of malicious traffic. At 280/100, this is an extremely high-risk address. All traffic should be considered hostile.
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.
Correlating logs across web servers, firewalls, DNS, and authentication systems reveals attack patterns invisible in individual log sources. Modern SIEM platforms use statistical analysis to connect related events across time and systems.