Chinese AI models are accelerating vulnerability pressure, and J.P. Morgan is bullish on incremental cybersecurity demand

Overview

This report focuses on the impact of improving AI model capabilities on the cybersecurity industry. J.P. Morgan believes that open-weight Chinese AI models are rapidly catching up in vulnerability discovery, and together with rising CVE volumes and faster exploitation, this will push enterprises to assess, manage, and remediate vulnerabilities in IT assets with greater urgency. As a result, exposure management vendors and security consolidation vendors with platform capabilities are expected to see incremental demand.

Core views

The core view is that the barriers to vulnerability discovery and exploitation are declining, and enterprise security budgets will increasingly flow to vendors that can cover assets, identify risks, automate remediation, and integrate security platforms. TENB is viewed as the best beneficiary in exposure management; QLYS will also benefit but is held back by execution and product mix migration; CRWD and PANW remain favored due to AI security, platform integration, and ecosystem positioning.

Analysis framework

The report combines AI cybersecurity capability benchmarks, CVE trends, product capabilities, customer migration potential, margins, free cash flow valuation multiples, and rating target prices to assess the relative benefit to each cybersecurity company in an environment of accelerating vulnerabilities.

Methodology notes

• Industry Driver AnalysisAI Vulnerability Discovery Capability and CVE Trends

  Use improvements in AI model capabilities and changes in CVE volume to judge whether enterprise security demand is accelerating.

  The report argues that Chinese models are catching up with frontier models in benchmark tests. Although there is still a gap in end-to-end autonomous attacks, the improvement in vulnerability discovery alone is already sufficient to increase enterprise exposure management pressure.

• Company ComparisonExposure Management Platform Migration

  Compare the differences between TENB and QLYS in customer base, product upgrades, AI agents, and two-way booking migration.

  TENB is seen as better positioned due to Tenable One, Hexa AI, Exposure Data Fabric, and larger upsell potential; QLYS has strong margins, but ETM and CSAM are increasing as a share more slowly.

• Valuation methodsEV/FCF and EV/Sales

  Derive target prices using forward free cash flow and sales multiples.

  TENB’s $40 target price is based on 14x EV/CY27E FCF and 3.7x EV/Sales; QLYS’s $139 target price is based on 13x EV/CY27E FCF.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• TENB

  Preferred beneficiary of accelerating exposure management demand

  Strengths

  Tenable One, Hexa AI, Exposure Data Fabric, a customer base of more than 40,000, and significant upsell potential.

  Weaknesses

  A substantial portion of revenue is still exposed to the lower-growth vulnerability management market.

  Comparison

  The report believes it is better able than QLYS to capture platform upgrade demand driven by accelerating vulnerabilities.

  Risks

  Federal government exposure, lower-priority spending, and execution risk from the new management team.

• QLYS

  Benefits from rising industry demand but with weaker elasticity than TENB

  Strengths

  High margins, more than 200mm agents, a multi-agent platform, and a sales focus on the Risk Operations Center.

  Weaknesses

  Slow two-way booking migration for ETM and CSAM, VMDR still accounts for a high proportion, and a lack of a long-term financial framework.

  Comparison

  The rating was upgraded from Underweight to Neutral, but the report still believes its ability to capture vulnerability tailwinds is weaker than TENB’s.

  Risks

  Sales execution pressure, slow two-way mix migration in bookings, and margin compression from sales and marketing investment.

• CRWD

  Beneficiary of AI security and platform integration

  Strengths

  Participates in Glasswing, OpenAI Daybreak, and Project QuiltWorks; AIDR covers a broader AI attack surface; Falcon can protect AI infrastructure at runtime.

  Weaknesses

  The excerpt does not provide a new target price or valuation details.

  Comparison

  Alongside PANW, it is one of the clearest platform beneficiaries in the report.

  Risks

  If AI security budget conversion is slow or platform integration falls short of expectations, estimate revisions upward may be limited.

• PANW

  Beneficiary of platform security consolidation and AI demand

  Strengths

  Early partner position in Glasswing, Cortex XSIAM integration capability, data flywheel, and expansion with CyberArk and Chronosphere.

  Weaknesses

  The excerpt does not provide a new target price or valuation details.

  Comparison

  Together with CRWD, it is viewed as one of the best-positioned platform consolidation vendors for AI-related incremental demand.

  Risks

  Integration complexity, false positives, and last-mile implementation issues may affect the pace of demand realization.

Key data

• TENB rating and target priceOverweight; Dec-27 target price $40.00; current price $33.49The target price implies about +19.4% upside versus the current price.
• QLYS rating and target priceUpgraded from Underweight to Neutral; Dec-27 target price $139.00; current price $128.32The target price implies about +8.3% upside versus the current price.
• Tenable One penetration rateAbout 30% of customers already use Tenable OneThe remaining roughly two-thirds, or a customer base of more than 40,000, provides upsell potential.
• Share of new business from Tenable One41% of new business in 1Q26The report states ASP improvement ranges from 6% to 60%.
• Qualys profitabilityAdjusted EBITDA margin 47%; Rule of 40 at 57%; FCF margin 45%Margins support valuation, but growth and mix migration remain key issues.
• QLYS business mix pressureETM and CSAM accounted for 11% of LTM bookings; VMDR still accounted for 50%The report believes slow mix migration limits its ability to capture upside from rising vulnerability demand.
• CRWD and PANWBoth remain OverweightThey benefit from AI security, platform integration, alliance positioning, and enterprise procurement screening demand.

Impact & implications

If AI models continue to improve in vulnerability discovery, cybersecurity demand may shift from routine vulnerability scanning toward more comprehensive exposure management, AI security runtime protection, and security operations platform integration. From an investment perspective, the report prefers companies that can combine vulnerability data, automated remediation, and platform-based sales, especially TENB, CRWD, and PANW.

Risks

• AI models still have limited real-world end-to-end autonomous attack capability, and performance on selected benchmarks does not equate to full autonomous attack capability.
• QLYS faces risks from sales execution, slow two-way booking mix migration, and margin compression.
• TENB faces risks from federal government exposure, lower-priority spending, and the new management team.
• If enterprise security budgets do not accelerate alongside rising vulnerability volumes and exploitation speed, industry demand elasticity may be lower than the report expects.
• The research institution discloses that J.P. Morgan has market-making, client, investment banking business, or potential compensation relationships with Qualys, Tenable, CrowdStrike, Palo Alto Networks, or related entities.

What to watch

• Whether CVE volumes and severity continue to rise in the remaining quarters of 2026.
• Changes in the capability gap between open-weight Chinese AI models and frontier models in real cybersecurity tasks.
• Whether TENB’s Tenable One penetration, Hexa AI adoption, and ASP improvement continue.
• Whether the share of QLYS bookings related to ETM, CSAM, and ROC can accelerate.
• CRWD’s AIDR demand, strategic customer penetration in AI security, and Falcon adoption in AI infrastructure.
• PANW’s Cortex XSIAM integration, CyberArk and Chronosphere synergies, and conversion of AI-related consulting demand.