This blog shows how bringing LLM-powered automation into policy management helps security and networking teams build, audit, and optimize network policies more efficiently. It integrates into existing workflows, offering real-time access to current configurations and intelligent policy insights — all without requiring teams to switch tools.
As organizations increasingly embrace AI-powered coding tools to accelerate development and reduce engineering overhead, a new threat is emerging at the intersection of generative AI and open-source software (OSS): slopsquatting.
OWASP Top 10 for Large Language Model (LLM) Applications, highlighting critical security vulnerabilities such as prompt injection, data poisoning, and system prompt leakage. It emphasizes the need for proactive security measures, including Zero Trust principles, access controls, and continuous monitoring to protect AI-driven applications from emerging threats.
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