
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| UA bot: python | Known bot/crawler User-Agent detected | +40 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 |
Reconstructed HTTP requests from server access logs. Target domains redacted for security.
* Typical request patterns for detected signatures. Actual target domains are redacted.
Address UA spoofing from 167.103.42.249: maintain blocklist of known malicious UA strings, require consistent UA across sessions, implement TLS fingerprinting.
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.
167.103.42.249 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:
Threat intelligence analysis has linked 167.103.42.249 to malicious activity originating from Tokyo, Japan, operating on the network of ZSCALER, INC.. The address has been under observation since its initial detection. Over a period of 1 days, this IP generated 1 malicious requests, averaging approximately 1 requests per day. This is a residential IP address, suggesting a compromised home device such as a router, smart appliance, or infected workstation participating in a botnet. The IP exhibits User-Agent manipulation, switching between different browser identities or sending empty headers. With 104 flagged addresses, Japan represents a significant presence in our threat database. The score of 65/100 warrants active monitoring and rate-limiting. Full blocking is advisable for sensitive systems.
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.
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.
Cloud platforms provide attackers with elastic, disposable infrastructure. Free tier accounts, stolen credit cards, and compromised cloud credentials enable rapid deployment of attack infrastructure that can scale to millions of requests and disappear within hours.