Stop Your Legacy Infrastructure from Hijacking Your AI Agents

What happened

Attackers are bypassing AI security programs by exploiting legacy infrastructure to hijack AI agents. This blind spot remains largely unaddressed in most security setups, despite AI’s rapid adoption across organizations. At the Gartner Security & Risk Management Summit, it was revealed that roughly 71% of companies are piloting AI agents, but many are not accounting for how older systems can undermine AI defenses.

The risk

Legacy infrastructure serves as a backdoor for attackers to manipulate AI agents outside the scope of modern AI security tools. Since AI is integrated with existing networks and systems, weaknesses in outdated platforms create an attack surface. This allows malicious actors to redirect, corrupt, or otherwise hijack AI functions, effectively nullifying AI-specific protections. Organizations with complex, aging environments face elevated risk because their AI security posture depends on outdated components they cannot easily replace.

Why it matters

The quick pace of AI deployment is outstripping security’s ability to keep up, making legacy infrastructure a critical vulnerability. Without addressing how older systems feed into AI workflows, organizations cannot fully trust AI agents or the decisions they automate. This gap raises operational risks, increases potential attack vectors, and potentially amplifies AI misuse. Teams managing AI security must extend protections beyond the AI layer to include legacy systems supporting AI agents.

Who should pay attention

Security teams, CIOs, and AI program leads must prioritize the legacy infrastructure risk when deploying or scaling AI agents. Simply adding AI-specific security controls is not enough; a holistic approach that audits and upgrades legacy systems tied to AI workflows is necessary to reduce attack surfaces. Builders and operators of AI agents also need to rethink integration strategies to isolate and protect AI functions from legacy vulnerabilities.

What to watch next

It will be important to track how organizations begin integrating legacy risk assessments into AI security frameworks. Watch for new tooling or frameworks aimed at bridging AI security and legacy infrastructure, as well as any regulatory moves that demand stricter oversight of legacy systems in AI environments. Progress in isolating AI agents from legacy weaknesses could reshape best practices for secure AI adoption.

AI Quick Briefs Editorial Desk