IP Threat Report
23.160.128.17
ABUSE.MOM — BEHAVE OR GET EXPOSED
Geolocation & Classification
Detection Signatures
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger medium hits: 4 | Medium-risk: admin panels, config files | +40 | |
| Probe pattern 302->404 same path | Behavioral anomaly detected by automated analysis | +20 | |
| Foreign referer seen | Referer from unrelated external domain | +10 |
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 23.160.128.17 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 23.160.128.0/24
- Report abuse to the network provider via their abuse contact
- Ensure sensitive files (.env, .git, backups) are not accessible from the web
🔎 Directory Scan Defense
IP 23.160.128.17 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
Neighbors in 23.160.128.0/24
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
Open Ports & Services
Network reconnaissance data from Shodan. Open ports may indicate running services, misconfigurations, or potential attack surfaces.
| Port | Service | Risk | Description |
|---|---|---|---|
| 4444 | Unknown | Low | Service on port 4444 |
| 8000 | Unknown | Low | Service on port 8000 |
| CVE ID | Link |
|---|---|
| CVE-2024-45802 | NVD → |
| CVE-2021-31806 | NVD → |
| CVE-2021-46784 | NVD → |
| CVE-2021-31808 | NVD → |
| CVE-2024-25617 | NVD → |
| CVE-2022-41317 | NVD → |
| CVE-2023-46847 | NVD → |
| CVE-2024-37894 | NVD → |
| CVE-2022-41318 | NVD → |
| CVE-2021-28662 | NVD → |
| CVE-2021-28116 | NVD → |
| CVE-2021-33620 | NVD → |
| CVE-2023-49288 | NVD → |
| CVE-2023-46846 | NVD → |
| CVE-2021-28652 | NVD → |
| CVE-2025-54574 | NVD → |
| CVE-2023-46728 | NVD → |
| CVE-2023-46724 | NVD → |
| CVE-2024-25111 | NVD → |
| CVE-2025-59362 | NVD → |
| CVE-2023-5824 | NVD → |
| CVE-2021-28651 | NVD → |
| CVE-2023-49285 | NVD → |
| CVE-2023-50269 | NVD → |
| CVE-2025-62168 | NVD → |
🔴 This host has 27 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 This volume strongly suggests severely outdated software.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.
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
23.160.128.17 has been assigned a threat score of 70/100 (High). This score indicates high threat severity. The IP has shown clear patterns of malicious behavior that warrant immediate defensive measures.
The following attack categories were identified:
📊 Threat Analysis
The address 23.160.128.17 originates from Los Angeles, United States, operating on the network of Sprious LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. During its 1-day observation window, we recorded 1 hostile requests from this IP — roughly 1 per day on average. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. United States currently accounts for 200 blocked IPs in our database, making it a significant source of malicious traffic. The score of 70/100 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.
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💡 Credential Stuffing at Scale
Credential stuffing uses stolen username-password pairs from data breaches to attempt logins across many websites. Since users frequently reuse passwords, these automated attacks achieve success rates of 0.1-2%, which translates to thousands of compromised accounts from millions of attempts.
💡 Behavioral Analysis vs Signature Detection
Signature-based detection matches known attack patterns but misses novel threats. Behavioral analysis identifies anomalies in request patterns, timing, and volume, catching zero-day attacks that signatures cannot recognize.