
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Form spam: no_js_check | Spam/malware keywords in request content | +0 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 78.118.225.75 is flooding forms with spam. Implement time-based tokens and block IPs submitting more than 5 forms per hour.
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.
78.118.225.75 has been assigned a threat score of 70/100 (High). This classifies it as a high-severity threat. Proactive blocking is recommended for sensitive infrastructure.
IP address 78.118.225.75 has been traced to Orvault, France, operating on the network of Societe Francaise Du Radiotelephone - SFR SA. Our threat detection systems have flagged this address based on observed malicious behavior patterns. 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. Our records show 135 malicious IPs originating from France, positioning it as a significant contributor to global threat activity. A threat score of 70/100 places this IP in the high-risk category. Blocking at the firewall level is recommended.
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.
SQL injection remains one of the most common web attack vectors. Attackers inject malicious SQL code through input fields to extract database contents, modify data, or gain administrative access. Automated scanners test for SQLi vulnerabilities at massive scale.
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.