
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| UA bot: curl | Known bot/crawler User-Agent detected | +40 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
IP 162.158.183.72 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
Other blocked IPs from the same /24 subnet — indicates systematic abuse from this network range.
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.
162.158.183.72 has been assigned a threat score of 65/100 (High). At this threat level, the IP is considered high risk. Firewall rules should be updated to deny traffic from this source.
The following attack categories were identified:
Network traffic from 162.158.183.72, located in Stockholm, Sweden, operating on the network of Cloudflare, Inc., has been classified as malicious by our automated threat scoring engine. Our sensors captured 25 malicious requests from this address across a 1-day span, reflecting a sustained attack cadence of ~25 requests per day. This IP is identified as a VPN or proxy endpoint, commonly used to mask the true origin of attack traffic and bypass geographic or reputation-based blocking. Detected suspicious User-Agent anomalies including empty, forged, or rapidly rotating UA strings — characteristic of automated scanning tools. Our records show 731 malicious IPs originating from Sweden, positioning it as a major contributor to global threat activity. The score of 65/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
This IP is associated with a VPN or proxy service. Attackers frequently route their traffic through anonymizing services to obscure their true location. This makes attribution more challenging but the malicious behavior patterns remain detectable.
SSRF attacks trick servers into making requests to internal resources that should not be publicly accessible. This can expose cloud metadata endpoints, internal APIs, and private network services, potentially leading to full infrastructure compromise.
Brute force attacks systematically try username and password combinations to gain unauthorized access. Modern attacks leverage credential databases from previous breaches, testing millions of combinations using distributed botnets across multiple IP addresses.