
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 6 | Medium-risk: admin panels, config files | +60 | |
| 404 ratio 40-60% | Majority of requests returned 404 — enumeration | +15 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Foreign referer seen | Referer from unrelated external domain | +10 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Block scanning from 147.78.53.152: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 80 | HTTP | Low | HTTP web server — standard web traffic |
| 3128 | Unknown | Low | Service on port 3128 |
| 8000 | Unknown | Low | Service on port 8000 |
| 8080 | HTTP-Alt | Low | HTTP alternative port — often used for admin panels or proxies |
| 8800 | Unknown | Low | Service on port 8800 |
| 21242 | Unknown | Low | Service on port 21242 |
| CVE ID | Link |
|---|---|
| CVE-2019-18860 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2023-46728 | NVD → |
| CVE-2019-12524 | NVD → |
| CVE-2024-45802 | NVD → |
| CVE-2022-41318 | NVD → |
| CVE-2020-8517 | NVD → |
| CVE-2021-31807 | NVD → |
| CVE-2020-25097 | NVD → |
| CVE-2020-14058 | NVD → |
| CVE-2020-15049 | NVD → |
| CVE-2025-62168 | NVD → |
| CVE-2019-12520 | NVD → |
| CVE-2019-18677 | NVD → |
| CVE-2019-18679 | NVD → |
| CVE-2021-31808 | NVD → |
| CVE-2023-49286 | NVD → |
| CVE-2021-28652 | NVD → |
| CVE-2020-8449 | NVD → |
| CVE-2018-1000024 | NVD → |
| CVE-2016-3947 | NVD → |
| CVE-2026-33526 | NVD → |
| CVE-2023-49285 | NVD → |
| CVE-2018-19131 | NVD → |
| CVE-2015-5400 | NVD → |
🔴 This host has 59 known CVEs associated with its exposed services. This volume strongly suggests severely outdated software. Review each CVE in the NVD database.
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.
147.78.53.152 has been assigned a threat score of 105/100 (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:
The address 147.78.53.152 originates from London, United Kingdom, operating on the network of XT GLOBAL NETWORKS LTD.. It was identified through automated analysis of incoming network traffic across monitored endpoints. The address has been active for 1 days in our monitoring system, producing 1 flagged requests at a rate of ~1/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. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. United Kingdom currently accounts for 30 blocked IPs in our database, making it a notable source of malicious traffic. With a threat score of 105/100, this IP is among the most dangerous addresses in our database. Immediate and complete blocking is strongly 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.
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.
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.