18:I[66739,["/_next/static/chunks/0u0nyy7wb9me2.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i","/_next/static/chunks/05hx6kuf6-oy4.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i","/_next/static/chunks/12hmyxte1w1dw.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i","/_next/static/chunks/166.u_60qj09..js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i","/_next/static/chunks/0g9_wl34k-6l4.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i","/_next/static/chunks/06dn~uer6.43l.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i"],"default"] 1a:I[38632,["/_next/static/chunks/0qqtp3r0h7kah.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i","/_next/static/chunks/0iukvycbd42rl.js?dpl=dpl_EVxQmm5ee6SfSwpTLEi7dkcqj48i"],"IconMark"] 19:T4df,

Current Large Language Model (LLM) agents are more powerful than ever, yet they remain fundamentally vulnerable to attacks like memory poisoning and context manipulation. Research shows that even high-performing models can fail to defend against prompt injection 85% of the time.

In our latest technical analysis, we cover:

Vulnerabilities: Why the "unreliable loop" of LLM agents creates entry points for data leakage.
AgentSandbox: A framework integrating classic security principles such as Least Privilege and Complete Mediation.
Defense-in-Depth: Why task-specific "ephemeral" agents are the future of secure AI workflows.

Securing the agentic future isn't just about better models; it's about better architectures.

Source Paper: https://arxiv.org/pdf/2505.24019 All my links: https://linktr.ee/learnbydoingwithsteven

#LLMs #AISecurity #AgenticAI #CyberSecurity #CloudSecurity #TechDiscussion #LearnByDoingWithSteven #StevenDataTalk #SecurityArchitecture #AIInnovation

Bridging the AI Security Gap: From Vulnerabilities to Principaled Defenses

Steven AI Talk

Bridging the AI Security Gap: From Vulnerabilities to Principaled Defenses