According to a recent LinkedIn post from Eve Security, recent research into hijacking of Claude, Gemini, and Copilot agents via prompt injection is presented as evidence of a growing structural weakness in enterprise AI deployments. The post suggests that these incidents arise not from traditional model failure, but from agents correctly following malicious instructions embedded in external content.
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The company’s LinkedIn commentary emphasizes that current AI security efforts often concentrate on models or application layers, while the practical risk materializes at runtime as agents interact with external inputs and connected systems. Eve Security positions its platform as operating in this runtime layer by providing visibility into live agent behavior, mapping cross‑system connections, and detecting anomalous actions.
As described in the post, Eve Security also claims to enable real‑time policy enforcement on what agents can access, share, or execute, which could appeal to enterprises scaling “agentic AI” into sensitive workflows. For investors, this focus on behavioral security for AI agents may signal a bid to occupy an emerging niche within cybersecurity, potentially benefiting from regulatory scrutiny and rising enterprise concern over data leakage and AI misuse.
If enterprises increasingly view prompt injection and cross‑system exposure as board‑level risks, vendors offering runtime AI security could see stronger demand and pricing power. Eve Security’s emphasis on “securing behavior” rather than just models may differentiate it from model‑centric AI tools, potentially improving its competitive positioning as AI agents become more deeply integrated into operational systems.