LLM Security articles
Articles, checklists and expert guidance on llm security from Aesparrow's penetration testers, auditors and compliance consultants.
Articles
OWASP Top 10 for LLM Applications 2026: Understanding the Biggest AI Security Risks
The OWASP Top 10 for LLM Applications 2026 identifies ten major security risks affecting AI-powered applications, including prompt injection, sensitive information disclosure, excessive agency, data and model poisoning, and improper output handling. Understanding these risks helps organizations…
OWASP GenAI Data Security Risks and Mitigations 2026
The OWASP GenAI Data Security Risks and Mitigations 2026 report examines data security risks across generative and agentic AI systems. It highlights sensitive data leakage, credential exposure, shadow AI, data poisoning, and weaknesses in retrieval systems, with practical measures to protect…
AI Red Teaming: Strengthening Generative AI Security Through Continuous Testing
AI red teaming helps organizations identify security weaknesses in generative AI models and autonomous agents before attackers exploit them. By simulating adversarial attacks, testing defensive controls, and monitoring system behavior, organizations can uncover risks such as prompt injection, data…
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