
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 | |
| Imported from old blocklist | Behavioral anomaly detected by automated analysis | +0 |
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 183.197.107.1: rate-limit 404 responses per IP, deploy a honeypot 404 page, ensure no backup files are web-accessible.
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.
183.197.107.1 has been assigned a threat score of 105/100 (Critical). A score this high marks a critical threat actor. This address has demonstrated persistent, aggressive malicious behavior across multiple detection vectors.
The following attack categories were identified:
The address 183.197.107.1 originates from Shijiazhuang, China, operating on the network of China Mobile. 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 3 flagged requests at a rate of ~3/day. The address belongs to a mobile carrier network. The sustained pattern of malicious requests indicates either a compromised device or deliberate abuse. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. With 112 flagged addresses, China represents a significant presence in our threat database. A score of 105/100 places this address in the top tier of severity. Block and investigate any historical connections.
Modern attacks increasingly target APIs rather than traditional web interfaces. Attackers enumerate endpoints, test for broken authentication, and exploit excessive data exposure. API attacks are harder to detect as they mimic legitimate programmatic access patterns.
Artificial intelligence enables more convincing phishing content, faster vulnerability discovery, and adaptive attack strategies that learn from defensive responses. AI-generated social engineering and automated exploit development represent growing threats.