Prompt Engineering for Security Agents: A Measurable Approach with GEPA
specterops.io | blog | #ai-security
Summary
GEPA replaces LLM prompt guesswork with measurable optimization. See how SpecterOps applied the Genetic-Pareto framework to a CTF agent using optimize_anything to improve prompt engineering for security agents.
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--- id: 9409 title: "Prompt Engineering for Security Agents: A Measurable Approach with GEPA" source_domain: specterops.io source_url: "https://specterops.io/blog/2026/06/09/prompt-engineering-security-agents-gepa/" published_at: "2026-06-10T02:23:12Z" tags: ["ai-security"] phying_url: "https://phying.com/item/9409" lang: en --- # Prompt Engineering for Security Agents: A Measurable Approach with GEPA ## Summary GEPA replaces LLM prompt guesswork with measurable optimization. See how SpecterOps applied the Genetic-Pareto framework to a CTF agent using optimize_anything to improve prompt engineering for security agents. ## Intelligence Metadata - **Sources:** specterops.io - **Published:** 2026-06-10T02:23:12Z - **Original:** https://specterops.io/blog/2026/06/09/prompt-engineering-security-agents-gepa/ - **Phying News:** https://phying.com/item/9409