
ABUSE.MOM — BEHAVE OR GET EXPOSED
| Signature | Description | Points | Severity |
|---|---|---|---|
| 404 ratio >= 60% | Majority of requests returned 404 — enumeration | +25 | |
| Danger strong hits: 1 | High-risk paths: shells, RCE vectors, exploits | +25 | |
| Foreign referer | Referer from unrelated external domain | +10 |
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 177.34.156.72: 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.
177.34.156.72 has been assigned a threat score of 60/100 (High). The IP is rated as a high-level threat. Network administrators should implement blocking rules and monitor for any connections from this address.
The following attack categories were identified:
Network traffic from 177.34.156.72, located in Franca, Brazil, operating on the network of Claro NXT Telecomunicacoes Ltda, has been classified as malicious by our automated threat scoring engine. Our sensors captured 437 malicious requests from this address across a 5-day span, reflecting a sustained attack cadence of ~87.4 requests per day. This residential IP is likely a compromised consumer device. Home routers and IoT equipment with default credentials are prime targets for botnet operators. Active path scanning has been detected — this IP probes for hundreds of common file and directory names. Our records show 110 malicious IPs originating from Brazil, positioning it as a significant contributor to global threat activity. The score of 60/100 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.
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.
Cryptojacking hijacks computing resources to mine cryptocurrency without consent. Indicators include unusual CPU usage, specific network connections to mining pools, and JavaScript miners embedded in compromised websites. Server-side cryptojacking can persist undetected for months.