Agentic Exposure Management: Revolutionizing Vulnerability Management with Agentic AI

Today's cybersecurity landscape is overwhelming. Organizations face millions of potential vulnerabilities, misconfigurations, and hidden risks that traditional vulnerability management tools struggle to address. Alarmingly, around 60% of breaches occur due to unpatched vulnerabilities, and there’s a 34% year-over-year rise in vulnerability exploitation. Yet, security teams in enterprises are forced to dedicate more than 130 hours weekly running arduous vulnerability management programs, addressing the exposures that actually matter to their organization. Compounding this challenge is a stark cybersecurity talent shortage currently estimated at 4.7 million unfilled security roles.

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This perfect storm demands a smarter, more efficient approach to managing cyber risk. Agentic AI presents revolutionary capabilities – that we’re leveraging at Tonic – to super-charge Exposure Management with advanced analytics, insights, recommendations, and proactive decision making.

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Why Agentic AI?

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Unlike traditional machine learning solutions and analytics tools, LLM-based agents operate in a more autonomous fashion, vastly simplifying complex tasks related to knowledge creation and decision making. It acts like a tireless, ever-vigilant digital analyst, continuously monitoring issues and threats, prioritizing critical findings, and suggesting or even initiating remediation steps. This moves organizations away from reactive, manual firefighting toward proactive, continuous defense.

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Agentic AI, built on the huge progress manifested in LLMs and multi-agent architectures, leverages large and diverse data such as institutional knowledge, asset databases, threat intelligence feeds, and configuration data to quickly suggest insights and make decisions. By continuously adapting and learning from the environment, agentic AI significantly reduces false positives and noise, allowing security teams to focus solely on genuine, impactful threats.

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Transforming Exposure Management

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Exposure management, as structured by Gartner's Continuous Threat Exposure Management (CTEM) framework, involves five key phases: Scoping, Discovery, Prioritization, Validation, and Mobilization. Agentic AI drastically enhances each phase:

1. Scoping: AI autonomously inventories assets, mapping their criticality based on business context, ensuring continuous and accurate identification.
2. Discovery: In addition to periodic vulnerability scans, agentic AI helps to continuously identify anomalies and deficiencies in real-time across networks, cloud services, compute assets, and shadow IT.
3. Prioritization: By considering exploitability, business impact, and live threat intelligence, agentic AI significantly reduces alert fatigue by highlighting only genuinely critical vulnerabilities.
4. Validation: Agentic AI autonomously validates defenses through simulations, ensuring vulnerabilities are genuinely exploitable and that patches effectively mitigate risk.
5. Mobilization: AI-driven workflow orchestration accelerates remediation efforts by automatically assigning tasks, opening tickets, and even executing immediate fixes when within policy.

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Should You Build or Buy?

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Organizations considering agentic AI face a critical decision: develop in-house or purchase from specialized vendors? Our (not so objective take):

• Building In-house: Tailored solutions offer deeper customization but require substantial expertise, time, and resources, typically viable only for large tech-driven enterprises. And even for these, maintaining homegrown solutions – albeit based on commercial foundational models - can be a pain, and companies run the risk of accumulating tech debt.
• Buying Commercially-of-the-Shelf (COTS) tools: Leveraging external specialist platforms provides rapid deployment, mature AI systems tested across diverse environments and operational use cases, ongoing support, and immediate integration into existing security ecosystems.Most organizations benefit from Best-of-Breed vendor solutions (at least initially), combining quick wins and proven capabilities while potentially developing niche customizations internally over time.

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Strategic Benefits for CISOs

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CISOs championing agentic AI solutions can expect clear benefits:

• Efficiency and Scalability: AI dramatically accelerates exposure management processes, reducing manual workloads, shortening response times, operating at hyper-scale, and enabling continuous monitoring.
• Enhanced Accuracy and Prioritization: Context-aware prioritization improves resource allocation, directly reducing genuine risks rather than chasing low-impact vulnerabilities that are fueled by generic security scores.
• Strategic Business Alignment: Agentic AI can help align security efforts more closely with core business objectives, ensuring critical assets and processes receive prioritized protection.

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Risks and Mitigation

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As with any powerful technology, agentic AI also introduces specific risks:

• Trust and Transparency: Autonomous decision-making requires strong governance and explainability to build stakeholder trust, particularly early on.
• Integration Complexity and Sensitivity: Ensuring seamless integration with existing diverse IT environments requires careful evaluation, and proper security and privacy guardrails.
• Over-Reliance: Security teams must remain vigilant against automation complacency, maintaining robust oversight and human-in-the-loop processes, especially initially.

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The Path Ahead: Industry Adoption

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Agentic AI adoption in cybersecurity is accelerating rapidly across sectors. Technology and finance organizations lead due to their large digital footprints and compliance pressures. Healthcare, energy, and manufacturing sectors follow, driven by escalating cyber threats despite an increasingly hybrid environment. Even traditionally slower sectors like retail and transportation recognize the transformative potential of autonomous cybersecurity solutions, driven by rising risks and digitization.

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Conclusion

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Agentic AI represents a strategic evolution in cybersecurity, helping transform vulnerability management from reactive firefighting to pre-emptive, continuous exposure management. By supercharging security teams in identifying, prioritizing, validating, and remediating threats, agentic AI empowers organizations to scale their security operations effectively, addressing today's rapidly evolving threat landscape with agility, precision, and unprecedented efficiency.

At Tonic, we leverage Agentic AI to enable security teams to proactively discover, assess, prioritize, and remediate findings and risks. Our AI gents can perform tasks, offer insights, and recommend or make decisions across the exposure management lifecycle – from scoping, discovery, prioritization, validation, to mobilization. This approach enhances efficiency, accuracy, and speed, while minimizing manual intervention, but keeping the human in the loop as needed. Learn more.

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