
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 4 | High-risk paths: shells, RCE vectors, exploits | +100 | |
| UA suspicious | Behavioral anomaly detected by automated analysis | +15 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 105.158.101.199 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
105.158.101.199 has been assigned a threat score of 115/100 (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:
Our monitoring infrastructure has identified 105.158.101.199, geolocated to Marrakesh, MA, operating on the network of ADSL Maroc telecom, as a source of suspicious network activity. During its 1-day observation window, we recorded 13 hostile requests from this IP — roughly 13 per day on average. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. Our records show 111 malicious IPs originating from MA, positioning it as a significant contributor to global threat activity. At 115/100, this is an extremely high-risk address. All traffic should be considered hostile.
This IP is classified as residential, suggesting it may belong to a compromised home device, IoT botnet member, or an infected personal computer. Residential IPs involved in attacks often indicate malware infection without the owner's knowledge.
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.
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.