
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 4 | High-risk paths: shells, RCE vectors, exploits | +100 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Add 41.249.21.33 to your firewall blocklist. Review logs for successful connections. Enable comprehensive logging on all public-facing services.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 7547 | Unknown | Low | Service on port 7547 |
Data source: Shodan InternetDB. Scanned independently of abuse.mom.
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.
41.249.21.33 has been assigned a threat score of 100/100 (Critical). With this rating, the IP falls into the critical severity bracket — among the most dangerous addresses in our monitoring database.
Our monitoring infrastructure has identified 41.249.21.33, geolocated to Rabat, MA, operating on the network of ADSL Maroc telecom, as a source of suspicious network activity. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. Operating from a residential network, this IP may represent a compromised home gateway or IoT device that has been drafted into a larger attack infrastructure. With 111 flagged addresses, MA represents a significant presence in our threat database. A score of 100/100 places this address in the top tier of severity. Block and investigate any historical connections.
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.
SSRF attacks trick servers into making requests to internal resources that should not be publicly accessible. This can expose cloud metadata endpoints, internal APIs, and private network services, potentially leading to full infrastructure compromise.
Analyzing network flows (NetFlow, sFlow, IPFIX) provides visibility into traffic patterns without inspecting packet contents. Flow data reveals scanning activity, data exfiltration, lateral movement, and command-and-control channels at scale.