
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +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 157.22.72.60 is enumerating directories. Configure fail2ban apache-404 jail after 10+ 404 errors. Disable directory listings. Normalize all 404 responses.
IP 157.22.72.60 shows suspicious UA behavior. Block empty User-Agent requests. Implement JavaScript-based bot detection for sensitive endpoints.
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.
157.22.72.60 has been assigned a threat score of 65/100 (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:
The address 157.22.72.60 originates from Cookstown, United Kingdom, operating on the network of Global Transit Systems LLC. It was identified through automated analysis of incoming network traffic across monitored endpoints. During its 1-day observation window, we recorded 70 hostile requests from this IP — roughly 70 per day on average. The address operates as a VPN/proxy exit node. Attackers route traffic through anonymizing services to obscure their real location and evade IP-based security controls. Two attack patterns were identified (Path Enumeration and User-Agent Anomaly), suggesting a semi-automated campaign that targets multiple vulnerabilities. At 65/100, this IP presents a meaningful threat. Implement rate limiting with escalation to blocking.
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.
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.
False positives erode trust in security systems and waste analyst resources. Effective management requires feedback loops, allowlisting mechanisms, contextual analysis, and regular tuning of detection rules based on operational experience.