How Security Teams Are Reclaiming Control Over Vulnerability Remediation

Lahav Ezer, Product Manager

April 15, 2025

5 min read

From Visibility to Resolution—Without the Bottlenecks In Between

Security teams today have no shortage of data. Cloud, code, and infrastructure scanners offer constant streams of vulnerability findings. But surfacing issues isn’t the hard part anymore, resolving them is.

Most organizations still rely on manual triage, unclear ownership, and reactive ticket queues to handle remediation. The result isn’t failure—it’s friction: slowed progress, strained teams, and delayed fixes that increase exposure windows.

Now, a more intelligent path forward is emerging. With Agentic AI, remediation can scale like software—autonomously, policy-aware, and fully aligned with how your teams already work. It’s not about replacing your processes. It’s about empowering them.

What’s Holding Remediation Back?

Vulnerability management has evolved, but the way remediation happens hasn’t caught up. Even mature security teams find themselves navigating:

Manual triage loops that drain time and resources.
Unclear ownership, leading to delays and backlogs.
Siloed workflows between security, IT, and engineering.
Static prioritization models that don’t reflect real-world risk.
Ticket overload, without meaningful action.

The good news? These challenges don’t require a full overhaul. They require smarter coordination, clearer ownership, and adaptive remediation that can run continuously in the background.

Why Being “Proactive” Isn’t Always Enough

Many teams have progressed toward proactive vulnerability management—running campaigns, enriching findings, and shifting left where possible. But execution still relies heavily on manual effort and fragmented processes.

To truly keep up with modern attack surfaces, remediation needs to be more than proactive. It needs to be autonomous.

What Autonomous Remediation Looks Like with Agentic AI

Agentic AI transforms remediation from a human-led task list into a self-directed system. Instead of just pushing tickets, AI agents identify what matters most, assign it to the right team, and resolve it—continuously and with full transparency.

Here’s how it works in practice:

1. Contextual Visibility Across Every Surface

Opus consolidates and normalizes findings from over 100 security tools. Then, AI agents add technical, organizational, and threat context—so you see the full picture, not just raw alerts.

2. Multi-Layer Risk Prioritization

Prioritization goes beyond CVSS. Our engine factors in exploitability, business impact, asset criticality, and real-time threat intelligence, so engineering and IT teams work on what’s actually urgent.

3. Intelligent Ownership Assignment

Remediation doesn’t move if no one owns it. Opus’ Organizational Context Agent instantly maps every vulnerability to the right person or team, reducing bottlenecks and cutting time to action.

4. Flexible Execution Paths

Each fix can follow the path your team prefers:

Fully autonomous remediation for low-risk or well-understood issues.
Semi-automated workflows with approvals built in.
Manual guidance embedded into Jira, Slack, or your existing tools.

5. Continuous Optimization

Every remediation informs the next. Opus AI agents learn from outcomes—refining prioritization logic, adjusting team preferences, and improving resolution speed over time.

From Findings to Campaigns to Fixes

Instead of triaging vulnerabilities one-by-one, security teams can group findings by type, asset, or risk profile—and run campaign-style remediations.

For example:

Group misconfigured IAM policies across cloud accounts and assign them to a single engineering team.
Bundle container vulnerabilities originating from the same Dockerfile and fix them at the source.
Launch SLA-driven patching initiatives that automatically escalate unaddressed issues.

This campaign-based model, orchestrated by Opus agents, provides structure, scale, and outcome tracking—without adding overhead.

Fix Once. Prevent Repeats.

Most vulnerabilities aren’t unique—they’re recurring misconfigurations, code patterns, or dependency risks that show up in multiple places. With Opus:

AI agents trace vulnerabilities back to their true origin, such as shared infrastructure or base images.
Fixing the root causes results in a wider blast radius of impact, eliminating duplicates across environments.
Security teams reduce noise and accelerate compliance by proactively addressing issues before propagate.

Aligning With the Teams Who Build and Maintain

Autonomous remediation doesn’t mean bypassing humans, it means empowering them. With Opus:

Developers only see relevant findings in their tools with precise guidance.
IT teams receive policy-aligned patching tasks within existing maintenance cycles.
Security leaders define the governance: when to automate, when to approve, and where to intervene.

Every action is logged. Every fix is mapped to policy. And every team operates in sync.

The Real-World Impact

Teams using Opus see measurable results:

Faster remediation with drastically reduced MTTR.
Smaller backlogs, thanks to campaign-based resolutions.
Clear ownership eliminates the delays of guesswork.
More time for strategic security work, as repetitive tasks are handled autonomously.

It’s not just about doing more—it’s about spending time on what matters most.

Conclusion: Autonomous Doesn’t Mean Out of Your Hands

Agentic AI isn’t here to replace the way you work. It’s here to remove the manual friction slowing you down. With Opus, you can:

Define how and when remediation happens.
Enforce your policies and compliance mandates.
Trust that every action is context-aware, audit-ready, and executed with precision.

Vulnerability management is no longer a chase. It’s a platform—always on, always improving, and built to work as your teams already do.

→ Explore how Opus works.

How Security Teams Are Reclaiming Control Over Vulnerability Remediation

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