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市場調查報告書
商品編碼
1891794
全球惡意軟體分析市場:依組件、部署模型、技術/分析類型、最終用戶行業、組織規模和地區進行分析 - 市場規模、行業趨勢、機會分析和預測(2026-2035 年)Global Malware Analysis Market: Analysis By Component, Deployment Model, Technique/Analysis Type, End-Use Industry, Organization Size, Region - Market Size, Industry Dynamics, Opportunity Analysis and Forecast for 2026-2035 |
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全球惡意軟體分析市場正經歷快速成長,是更廣泛的網路安全產業的重要組成部分。該市場在 2025 年的價值約為 146 億美元,預計將大幅擴張,到 2035 年將達到約 1,138 億美元。這一令人矚目的成長軌跡意味著在 2026 年至 2035 年的預測期內,複合年增長率 (CAGR) 將達到 22.8%。這一強勁成長凸顯了惡意軟體分析對於全球組織機構保護自身免受快速演變的網路威脅的重要性日益增加。
推動市場價值快速成長的關鍵因素有很多,其中最主要的是網路威脅的激增,其頻率和複雜性都在增加。網路犯罪分子不斷改進其策略,開發更複雜的惡意軟體,旨在規避傳統檢測方法並造成更大的破壞。隨著各行各業數位轉型加速,對互聯繫統和線上平台的依賴性日益增強,攻擊面也隨之擴大,因此,有效的惡意軟體分析對於保護敏感資料和確保業務連續性至關重要。
惡意軟體分析市場日益被少數幾家主要廠商所主導,前五大公司佔了約 45% 的市場佔有率。 Palo Alto Networks、Cloud Astrike 和 Trellix(前身為 FireEye/McAfee)等產業領導者正積極推行收購策略,並專注於利基人工智慧新創公司,以強化其 "平台化" 策略。這種做法反映出惡意軟體分析工具正從獨立的工具轉向整合到全面的擴展檢測與回應 (XDR) 生態系統中。
2025年9月,開源評估平台 "CyberSOCEval" 的發布吸引了網路安全界的廣泛關注。這個創新平台展現了人工智慧在惡意軟體分析和威脅情報方面的變革潛力。該平台能夠評估和測試人工智慧驅動的網路安全工具,幫助企業更了解新興技術的功能和有效性。
同樣在2025年9月,安信集團參與了Nucleon Security的300萬歐元種子輪後期融資,成為新聞焦點。 Nucleon Security是一家專注於智慧、整合和自動化網路安全解決方案的公司。此次投資將加速Nucleon零信任、基於代理的人工智慧平台的產業化,該平台強調自主決策和高階威脅緩解。
2025年7月,博思艾倫顧問公司推出了Vellox Reverser™,這是一款人工智慧雲端產品,旨在保護企業免受日益複雜的惡意軟體攻擊。 Vellox Reverser™ 利用點對點節點網路協作拆解複雜的惡意軟體二進位文件,並在幾分鐘內提供可操作的防禦建議——相比傳統分析耗時數天甚至數週,這是一個顯著的改進。
核心成長驅動因子
預計到 2025 年底,全球網路犯罪造成的損失將達到驚人的每年 10.5 兆美元,凸顯了惡意網路活動在全球範圍內帶來的巨大財務風險。這一驚人的數字反映了網路攻擊在各行各業日益增長的規模和影響,從資料外洩和勒索軟體事件到智慧財產權盜竊和關鍵基礎設施破壞。這些損失的規模之大與網路安全防禦支出的增加形成了強烈的直接關聯。各組織正努力加強其網路安全防禦,以保護自身免受不斷升級的威脅和成功攻擊的毀滅性後果。
新機會與趨勢
多態性從根本上改變了網路安全格局,使得傳統的基於特徵碼的檢測方法基本上過時。大約 93% 的現代惡意軟體都具有多態性,這意味著它們會在每次迭代中改變其底層程式碼結構,以逃避傳統的檢測技術。這種持續的變異使得依賴識別已知模式和程式碼片段的基於特徵碼的系統難以跟上不斷演變的威脅情勢。因此,企業越來越難以準確、快速地辨識惡意軟體,這需要一種更複雜、更具適應性的惡意軟體分析方法。
優化障礙
對抗性人工智慧是可能阻礙惡意軟體分析市場成長的重大挑戰。這種先進的人工智慧旨在透過模仿合法用戶的行為來逃避偵測,使得傳統的安全系統和惡意軟體分析工具極難識別惡意活動。與通常會表現出明顯入侵跡象的傳統惡意軟體不同,對抗性人工智慧以更微妙、更複雜的方式運行,與正常的網路流量和用戶活動無縫融合。這種偽裝能力對現有檢測方法的有效性構成了嚴重威脅。
The global malware analysis market is experiencing rapid growth and has become a vital segment within the broader cybersecurity industry. Valued at approximately US$ 14.6 billion in 2025, this market is projected to expand dramatically, reaching an estimated valuation of US$ 113.8 billion by 2035. This impressive growth trajectory corresponds to a compound annual growth rate (CAGR) of 22.8% during the forecast period from 2026 to 2035. Such robust expansion highlights the increasing importance placed on malware analysis as organizations worldwide strive to defend themselves against a rapidly evolving cyber threat landscape.
Several key factors are driving this surge in market value. Foremost among them is the escalating volume of cyber threats, which continue to grow in both frequency and complexity. Cybercriminals are constantly refining their tactics, developing more sophisticated malware designed to evade traditional detection methods and inflict greater damage. As digital transformation accelerates across all industries, the expanding reliance on interconnected systems and online platforms has created a broader attack surface, making effective malware analysis critical for safeguarding sensitive data and operational continuity.
The malware analysis market is increasingly dominated by a handful of major players, with the top five companies controlling roughly 45% of the total market share. Industry giants such as Palo Alto Networks, CrowdStrike, and Trellix (formerly FireEye/McAfee) are actively pursuing aggressive acquisition strategies, focusing on niche AI startups to enhance their broader "platformization" efforts. This approach reflects a shift away from standalone malware analysis tools, which are gradually being integrated into comprehensive Extended Detection and Response (XDR) ecosystems.
In September 2025, the cybersecurity community took note of the launch of Open Source CyberSOCEval, an innovative evaluation platform that showcases the transformative potential of artificial intelligence in malware analysis and threat intelligence. This platform is gaining traction for its ability to assess and benchmark AI-driven cybersecurity tools, helping organizations better understand the capabilities and effectiveness of emerging technologies.
Also in September 2025, AXIAN Group made headlines by participating in a €3 million late seed funding round for Nucleon Security, a company specializing in intelligent, integrated, and automated cybersecurity solutions. This investment is poised to accelerate Nucleon's efforts to industrialize its Zero Trust agentic AI platform, which emphasizes autonomous decision-making and advanced threat mitigation.
In July 2025, Booz Allen Hamilton unveiled Vellox Reverser(TM), an AI-enabled cloud product designed to protect organizations against increasingly sophisticated malware attacks. Leveraging a network of peer-to-peer nodes, Vellox Reverser(TM) collaboratively deconstructs complex malware binaries and delivers actionable defensive recommendations within minutes, a significant improvement over traditional analysis timelines that can take days or even weeks.
Core Growth Drivers
Global cybercrime costs are projected to reach an astonishing US$ 10.5 trillion annually by the end of 2025, underscoring the immense financial risks posed by malicious cyber activities worldwide. This staggering figure reflects the growing scale and impact of cyberattacks across industries, from data breaches and ransomware incidents to theft of intellectual property and disruption of critical infrastructure. The sheer magnitude of these losses has created a strong and direct correlation with increased spending on cybersecurity defenses, as organizations strive to protect themselves from escalating threats and the devastating consequences of successful attacks.
Emerging Opportunity Trends
Polymorphism has fundamentally transformed the cybersecurity landscape by rendering traditional signature-based detection methods largely obsolete. Approximately 93% of modern malware strains exhibit polymorphic characteristics, meaning they alter their underlying code structure with each new iteration to evade conventional detection techniques. This constant mutation makes it extremely challenging for signature-based systems, which rely on identifying known patterns or code snippets, to keep up with the evolving threat landscape. As a result, organizations face increased difficulty in accurately and swiftly identifying malicious software, necessitating more advanced and adaptive approaches to malware analysis.
Barriers to Optimization
Adversarial AI represents a significant challenge that could potentially hamper the growth of the malware analysis market. This advanced form of artificial intelligence is designed to evade detection by mimicking legitimate user behavior, making it exceptionally difficult for traditional security systems and malware analysis tools to identify malicious activity. Unlike conventional malware that often exhibits clear signs of intrusion, adversarial AI operates in a more subtle and sophisticated manner, blending seamlessly with normal network traffic and user interactions. This ability to disguise itself poses a serious threat to the effectiveness of existing detection methodologies.
By Technique, Dynamic analysis currently holds a significant and influential position within the malware analysis market, commanding a substantial 34.85% share by technique. This prominence is largely due to the limitations of traditional static analysis methods, which struggle to keep pace with the rapidly increasing volume and complexity of modern cyber threats. Static analysis, which involves examining malware code without executing it, often falls short when confronting sophisticated malware that employs obfuscation, encryption, or polymorphic techniques designed to evade detection. These advanced threats require a more adaptive and interactive approach to uncover their true behavior and potential impact.
By End Use Industry, the Banking, Financial Services, and Insurance (BFSI) industry stands out as the most prominent consumer in the malware analysis market, capturing the highest share at 35.78%. This dominant position is a direct consequence of the industry's status as a prime target for sophisticated financial crimes. Given the vast amounts of sensitive personal and financial data handled daily, BFSI organizations are constantly at risk from cybercriminals seeking to exploit vulnerabilities for monetary gain. The high stakes involved in protecting customer assets, maintaining regulatory compliance, and preserving trust make robust malware analysis an essential component of their cybersecurity strategies.
By Deployment, Cloud deployment has emerged as the leading choice in the malware analysis market, capturing over 48% of the share by deployment type. This dominance is largely attributed to the flexibility and scalability that cloud-based solutions provide, allowing security teams to overcome the limitations imposed by traditional hardware infrastructures. Unlike on-premises systems, which require significant investment in physical servers and maintenance, cloud deployments enable organizations to leverage powerful computational resources on demand without the burden of managing complex hardware setups.
By Component
By Technique/Analysis Type
By Deployment Model
By Organization Size
By End-Use
By Region
Geography Breakdown