Why Agentic AI is the Future of Vulnerability Management

Meny Har, Co-Founder & CEO

March 13, 2025

5 min read

Despite improvements in automation, traditional vulnerability management remains reactive and inefficient. Findings pile up across cloud, applications, infrastructure, and identity, while security teams spend hours manually triaging, assigning, and chasing fixes.

The reality facing security teams today includes:

60% of breaches coming from unpatched vulnerabilities.
Teams spending over 130 hours weekly on manual remediation tasks.
Millions of vulnerabilities piling up across cloud, applications, infrastructure, and identity surfaces.

Traditional vulnerability management practices are outdated and inadequate. Security teams need an innovative, scalable approach to meet today’s challenges head-on.

Too Many Vulnerabilities, Not Enough Context

Every year, new attack surfaces emerge as organizations expand their cloud environments, adopt AI-driven technologies, and integrate identity and data-centric security models. With these innovations come an ever-growing number of vulnerabilities—many lacking the context needed for effective remediation.

Security teams are not just overwhelmed by volume; they struggle to distinguish real threats from noise. Traditional risk scoring models fail to account for business impact, exploitability, and active threats in the wild. As a result, teams face:

Misprioritization - focusing on low-risk vulnerabilities while critical issues remain unaddressed.
Alert fatigue - drowning in thousands of findings without clear guidance on what matters most.
Remediation delays - spending more time triaging than actually fixing security gaps.

With identity, AI, and data security now introducing additional layers of complexity, traditional vulnerability management approaches are no longer scalable. Security teams need trusted prioritization, adaptive processes and intelligent automation that cuts through the noise and ensures vulnerabilities are remediated before they become threats.

Remediation Has Evolved—But Workflows Haven’t

Vulnerability remediation is no longer just a security function—it requires seamless collaboration across security, IT, and engineering teams. As attack surfaces grow and vulnerabilities span cloud, applications, identity, and AI systems, remediation must align with modern organizations' operations.

Yet, most remediation workflows remain outdated and disconnected. Security teams identify vulnerabilities, IT teams own patching, and engineering teams manage code fixes—but they rarely work in sync. This lack of alignment leads to:

Ownership confusion - unclear responsibility for fixing vulnerabilities, leading to delays.
Workflow rigidity - static ticketing and approval processes that do not adapt to business needs.
Ticket-Driven, Context-Blind - security pushing remediation tasks without the necessary context or in-depth understanding of the environment making it harder for remediation teams to act efficiently.

Security teams cannot fix vulnerabilities alone. Without proactive coordination, technical expertise, and intelligent automation to close the gaps, remediation remains slow, fragmented, and reactive—allowing preventable threats to slip through and put organizations at risk.

The Hidden Cost of Reactive Security

Security teams remain stuck in a cycle of reacting to vulnerabilities rather than proactively resolving them. This reactive approach fuels security debt, where unresolved vulnerabilities accumulate faster than teams can fix them—creating a growing risk backlog.

The result? SLA breaches, increased exposure, and operational drain.

Traditional automation has failed to break this cycle. Simply generating tickets and moving data between systems is not enough. Security teams need a smarter approach that prioritizes, orchestrates, and executes remediation dynamically, ensuring vulnerabilities are fixed before they become threats.

From Automation to True Autonomy

Traditional automation in vulnerability management is limited—it follows predefined workflows, moves data between tools, and generates tickets, but it doesn’t think, adapt, or resolve issues. Security teams are still forced to manually coordinate remediation, making the process slow and reactive.

True autonomy goes beyond automation—it enables AI security agents to analyze, prioritize, assign, and execute remediation dynamically, ensuring vulnerabilities are addressed efficiently, at scale, and without constant human intervention.

Automation ≠ Autonomy.

Automation simply moves data around. Scanning for vulnerabilities, creating tickets, and triggering basic remediation workflows. But it doesn’t think, adapt, or execute remediation intelligently. Autonomous security is goal-driven, not task-based. It ensures that security outcomes—not just security workflows—are optimized for speed, accuracy, and efficiency.

What Makes Agentic AI Different?

Agentic AI doesn’t just automate tasks—it actively analyzes, prioritizes, and resolves vulnerabilities based on real-world risk.

Understands security policies and risk frameworks
Determines – prioritizes the most critical risks, and decides when and who to engage
Engages the right teams automatically
Collaborates or executes remediation directly
Learns from past actions to optimize workflows

This shift from manual intervention to autonomous execution is the key to scaling security without increasing operational burdens.

How Opus AI Agents Fix Vulnerabilities at Scale

Managing vulnerabilities across modern attack surfaces demands intelligence, adaptability, and execution at scale—far beyond what traditional automation can offer. AI security agents transform vulnerability management from a fragmented, manual process into a self-driven, autonomous operation. These agents don’t just process data; they act on it, ensuring vulnerabilities are identified, prioritized, and remediated efficiently—without bottlenecks or manual coordination.

Full Visibility Across Every Attack Surface
The platform integrates with 100+ security tools, consolidating, normalizing, and analyzing vulnerabilities across cloud, applications, infrastructure, and identity environments.
Real-Time Risk-Based Prioritization
Prioritization goes beyond CVSS scores. AI security agents leverage our Multi-Layer prioritization engine and assess exploitability, active threat intelligence, and business impact to determine what truly needs to be fixed first.
Dynamic and Self-Driven Remediation Orchestration
Opus’ AI agents automate the coordination between security, IT, and engineering, dynamically assigning ownership, enforcing security policies, and ensuring fixes align with existing workflows like IT patching cycles and engineering sprints.
Agentic AI Fix Execution
Unlike traditional automation that simply moves data between systems, Opus’ AI security agents offer flexible remediation options. They can execute fixes autonomously when approved, provide guided remediation workflows for collaboration, or suggest actionable solutions—ensuring teams stay in control while maintaining alignment with security and compliance mandates.
Continuous Learning and Optimization
The AI security agents learn from every remediation action taken, refining workflows, accelerating response times, and optimizing prioritization models over time.

This isn’t just automation. It’s autonomous, intelligent, and always-on vulnerability management that eliminates backlogs, reduces risk exposure, and enables security teams to focus on strategy—not endless remediation.

Security Stays in Control

Autonomy does not mean losing oversight. Security leaders retain full governance, visibility, and control over remediation processes. AI security agents operate within predefined policies, escalation rules, and compliance mandates, ensuring that remediation aligns with organizational risk frameworks. Flexible approval points allow security teams to define exactly where AI operates independently and where security teams take the lead, ensuring a structured and controlled remediation process. Every action is logged and auditable in real-time, providing transparency and accountability at every step.

By combining a proven security platform with AI agents, organizations can gradually expand autonomy with trust. Security teams decide where automation runs the process and where security team-led workflows remain in place, allowing AI to handle routine fixes while keeping critical decisions in their hands. This balance ensures remediation accelerates without compromising governance, risk management, or operational workflows. Automation grows within your existing framework—not outside it.

Embrace Agentic AI

Vulnerability management does not scale manually.

Security teams have been stuck in reactive, inefficient workflows for too long—chasing alerts, managing backlogs, and struggling to keep up.

Agentic AI changes the game.

With Opus, vulnerability management is no longer an endless cycle of detection and triage.
It becomes an autonomous, always-on security operation—resolving vulnerabilities at scale while keeping security teams in control.

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Why Agentic AI is the Future of Vulnerability Management

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