Navigating AI vulnerability discovery and achieving operational resilience with automation

It’s no secret that AI-fueled research projects are placing a spotlight on vulnerabilities across the industry. While large catalogs of vulnerabilities have been created, automation plays a key role in your organization’s ability to address them before they impact the business. When patches for vulnerabilities exist, they should be triaged and applied. Customers have also accelerated patching cycles to handle more of these patches more quickly. 

 In this blog, I will detail a series of mitigations and techniques you can use to address areas where patches are forthcoming but not yet present, as well as patching production environments in this dynamic world. These strategies are in addition to good perimeter defenses and comprehensive clearinghouse and “find-and-fix” patching initiatives, including IBM and Red Hat’s recently announced Lightwell. 

You can align these practices around the common recommended phases for incident response: Containment, eradication, and recovery. Each phase can be treated as a deliberate, repeatable process, which is precisely what automation is built for. 

Phase 1: Containment 

When a vulnerability has been identified but there are no available patches, the first step to mitigate the threat is containment. Containment could mean many things, such as isolation, restricting access, disabling accounts of vulnerable services, or revoking credentials. Containment can also include hardening surrounding infrastructure or moving critical workloads to other platforms. Automating these tasks creates a rapid response workflow when time is of the essence. 

Let’s look at a few examples: 

Example 1: Contain now, patch when ready 

Your vulnerability scanner triggered an alert to the event-driven automation capabilities included in Red Hat Ansible Automation Platform. This alert provides all the relevant information such as the vulnerability’s severity and scoring data, which are mapped against the conditions in the rulebook you defined. When you meet the conditions in the rulebook, Event-Driven Ansible triggers a workflow that moves the system onto an isolated virtual local area network (VLAN) for quarantine, restricts port or network traffic, and applies a stricter firewall configuration. 

Once the patch is available, Ansible Automation Platform automates the process of removing these controls and applies the patch in a controlled manner, including at-scale. This deterministic approach provides a repeatable, automated way of containing systems that is auditable and can include human-in-the-loop approval steps. 

This phased approach can be your standard, automated method of responding rapidly to a new threat that initially had no patch. This automation can integrate with your security information and event management (SIEM) and observability infrastructure, allowing you to go quickly from insight into action with speed and control. 

Example 2: Mitigations for business-critical workloads

Not every service lends itself to the process described in workflow example 1. Critical IT or application platforms might not be as forgiving to containment. How can we improve on this workflow dynamically? 

When a patch does not exist, experienced engineers typically reach for workarounds such as: disable a vulnerable feature, tighten firewall rules, redirect traffic, expand monitoring, or add authentication checkpoints. These are well-understood techniques. The problem has never been knowing what to do—it has been doing it fast enough, across enough systems, with enough confidence that the workaround does not break something else.

This is where Ansible Automation Platform’s generative AI assists. Integrating Ansible Automation Platform with AI tooling allows you to enhance response quality and speed. The included generative AI and Model Context Protocol (MCP) server can connect to security intelligence services to accelerate the entire cycle. Instead of an engineer manually researching common vulnerabilities and exposures (CVEs), writing a one-off remediation playbook, testing it on a single host, and then manually rolling it out, the workflow uses AI to expedite understanding of the CVE impacts, generate code (for testing), and remediate as desired. 

Figure 1: Using AI to generate vulnerability remediation playbooks 

In this diagram, event-driven automation receives the event and triggers an automation workflow. The first job in the workflow uses MCP to pull context from multiple sources. An MCP connection retrieves the CVE details, such as Common Vulnerability Scoring System (CVSS) score, affected package versions, and vendor-recommended mitigations. A second MCP connection to the organization's SIEM checks whether any exploit attempts have already been observed, and a third MCP connection to the configuration management database (CMDB) identifies every system running the affected package, its business criticality, and its team ownership.

That combined intelligence is packaged into an IT service management (ITSM) ticket as part of the same workflow. The technical team reviews the context and uses Ansible Automation Platform generative AI to generate a remediation playbook tailored to the specific vulnerability, the specific systems, and the compensating controls that are needed in their environment (including network segmentation, firewall rule updates, and disabling vulnerable services). The technical team can review and deploy the remediation with the necessary approval steps, and this entire cycle can be done in minutes instead of hours or days that it would take to accumulate and cross-reference these information sources manually. 

Introducing AI into the automated workflows does not replace technical teams’ judgment, but accelerates teams’ ability to act.

As teams create this automation content, they can review and test it before deploying.. With Ansible Automation Platform, you can also store this content as trusted, signed automation content, thus creating a source of truth for mitigating vulnerabilities until there’s an available patch. 

Phase 2: Eradication

Speed matters, but sustainable speed matters more. While containment limits the radius of affected systems, eradication removes the root cause. Once interim measures are in place and the immediate pressure is off, implementing the patch tends to slip down the priority list as technical teams move on to the next fire. By the time the vendor ships a fix weeks later, the context has evaporated—which systems were affected, what workaround was applied, what the rollback plan was.

Automation prevents this drift by making the patch a required step in the same workflow that performed containment, not a separate follow-up that depends on someone remembering.

• Store what you build
  • Every remediation playbook created during containment is automation content that has value beyond the current incident. Ansible Automation Platform's private automation hub provides a central repository for this content, and content signing verifies that the playbooks deployed to production are the same ones that were reviewed and approved. Teams gain access to tested, approved remediation for known CVEs instead of rebuilding the response from scratch each time.
• Extend the rulebook
  • The Event-Driven Ansible rulebook that triggered containment in Phase 1 should already have a second rule waiting for the patch event. Extending the conditions in your Ansible Rulebook and connecting them to the approved remediation playbooks enables these patterns to be handled consistently and automatically, drawing from your library of signed, tested content.
• Enforce policy before you patch at scale
  • Patches cannot simply be rolled out the moment they land. Production systems have maintenance windows, dependencies, and change management requirements. Policy-as-Code enforces governance and control before patches reach production. Human-in-the-loop approval nodes in the automation workflow help teams satisfy change management and compliance without slowing down the response.
• Let the audit trail do the reporting
  • Every job in Ansible Automation Platform produces a detailed execution log: each task, each change, each outcome recorded. Integrating ITSM lifecycle into the patching workflow allows automation to update tickets and change controls as it rolls out updates across the infrastructure.

Figure 2: Remediating CVEs with policy checks while creating velocity

Phase 3: Recovery 

While containment limits the damage and eradication removes the root cause, recovery is about restoring normalcy. Operational resilience means managing vulnerabilities without sacrificing the availability of the critical applications your business relies on.

Instead of treating recovery as a manual, post-patching checklist, you can extend your automation workflows to handle the entire validation and restoration process seamlessly. By integrating these final steps, your workflow safely returns systems to production:

• Automated system validation. Once a system is patched, automation natively verifies its health. This eliminates the need for manual testing by building programmatic checks directly into the workflow, complete with automated feedback loops and ITSM lifecycle integration.
• Programmatic health and posture checks. Before a remediated system goes live, Ansible Automation Platform checks the environment programmatically. It validates that applications are fully operational, configuration drift is minimized, and the correct security postures remain intact.
• Reversing containment measures. The same workflow that quarantined the threat can now safely dismantle those temporary defenses. It lifts network isolations, deactivates quarantine VLANs, and reverts restrictive firewall rules to restore normal traffic flow.
• Policy-driven governance. Policy checks act as the final automated gatekeeper, enforcing strict governance and compliance standards before any remediated system is permitted to handle production traffic again.

Figure 3: Automating recovery steps, including remediation, policy checks, verification and removing containment constructs. 

Threat actors are already leveraging AI to move faster, which means your defensive posture must do the same. Thriving in this new landscape requires moving beyond reactive measures. By automating the entire vulnerability’s lifecycle, from Day 0 containment to final recovery, you enhance business security posture and operations, no matter how fast the threat landscape evolves.

Resources

• Blog series:
  • Managing IT Operations when AI outpaces your patching cycle
  • AI threats move fast. Your defenses should too. 
  • Build security into ITOps from the start
• Interactive walkthrough security automation 
• Security automation web page
• Automate security, align ITOps webinar 
• Webinar: Implementing Zero Trust with Red Hat Ansible Automation Platform, July 2, 2026