
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| POST requests present | Behavioral anomaly detected by automated analysis | +8 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 45.234.9.67 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 2000 | Unknown | Low | Service on port 2000 |
| 2222 | Unknown | Low | Service on port 2222 |
| 8008 | Unknown | Low | Service on port 8008 |
| 8728 | Unknown | Low | Service on port 8728 |
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.
45.234.9.67 has been assigned a threat score of 83/100 (Critical). This represents a critical risk level. Our detection systems have flagged multiple high-confidence indicators of malicious intent from this address.
The following attack categories were identified:
Our monitoring infrastructure has identified 45.234.9.67, geolocated to João Pessoa, Brazil, operating on the network of Provedor de Acesso a Internet de Pernambuco Ltda, as a source of suspicious network activity. Our sensors captured 1 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~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. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. Our records show 101 malicious IPs originating from Brazil, positioning it as a significant contributor to global threat activity. The score of 83/100 indicates a confirmed malicious actor. Network-level blocking is appropriate.
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.
TLS fingerprinting creates unique identifiers based on how clients negotiate encrypted connections. The JA3 and JA4 methods generate hashes from TLS ClientHello parameters, enabling identification of specific tools and malware regardless of IP address changes.
Machine learning models analyze vast amounts of network traffic to identify attack patterns invisible to rule-based systems. Supervised models classify known attack types while unsupervised models detect anomalies that may indicate novel threats.