IP Threat Report
135.136.71.244
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Danger medium hits: 1 | Medium-risk: admin panels, config files | +10 | |
| Danger medium hits: 2 | Medium-risk: admin panels, config files | +20 | |
| Danger medium hits: 3 | Medium-risk: admin panels, config files | +30 | |
| Danger medium hits: 4 | Medium-risk: admin panels, config files | +40 | |
| Danger medium hits: 5 | Medium-risk: admin panels, config files | +50 | |
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| Foreign referer | Referer from unrelated external domain | +10 | |
| UA changed | Multiple User-Agents — bot rotation technique | +25 |
Observed Activity
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Timeline
Network Provider
Recommendations
Actions taken & recommended
- IP 135.136.71.244 is blocked at application level (HTTP 403)
- Consider blocking at firewall level (iptables/CSF) to reduce server load
- Other malicious IPs detected in the same /24 subnet — consider blocking 135.136.71.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🔎 Path Enumeration Protection
Block scanning from 135.136.71.244: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
🤖 Bot Detection
Address UA spoofing from 135.136.71.244: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
Neighbors in 135.136.71.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Blacklist Status (DNSBL)
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.
Threat Analysis
135.136.71.244 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.
The following attack categories were identified:
📊 Threat Analysis
Our monitoring infrastructure has identified 135.136.71.244, geolocated to Panama City, PA, operating on the network of M247 Europe SRL, as a source of suspicious network activity. The address has been active for 1 days in our monitoring system, producing 439 flagged requests at a rate of ~439/day. The IP is classified as hosting/datacenter infrastructure, commonly associated with rented servers used for automated attack campaigns, botnet command-and-control, or vulnerability scanning at scale. Two attack patterns were identified (Path Enumeration and User-Agent Anomaly), suggesting a semi-automated campaign that targets multiple vulnerabilities. With 51 flagged addresses, PA represents a notable 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 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.
Related Threats
Security Intelligence
💡 Command Injection Techniques
Command injection occurs when attackers insert operating system commands through application inputs. Successful exploitation grants direct server access, enabling data theft, malware installation, and lateral movement across networks.
💡 Web Application Firewall Strategies
WAFs inspect HTTP traffic to block common attacks but require careful tuning. Overly aggressive rules cause false positives while permissive configurations miss attacks. Modern WAFs combine signature matching with behavioral analysis and machine learning.