Latest research in security attacks in Wireless Sensor Networks focuses on identifying, preventing, and mitigating threats such as sinkhole, Sybil, wormhole, and selective forwarding attacks that compromise data integrity and network performance. Recent studies propose lightweight cryptographic algorithms, trust-based routing, and intrusion detection mechanisms to enhance security within resource-constrained environments. Machine learning and blockchain-based approaches are also being integrated to detect anomalies, ensure secure communication, and maintain energy efficiency, thereby strengthening overall resilience against evolving cyber threats in WSNs.