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SD-WANの計画と実施におけるセキュリティ統合の重要性

世界的なサイバー脅威の状況は、報告される攻撃件数が増加の一途をたどるなど、企業にとって引き続き懸念事項となっている。昨年は、被害者に公開恐喝を行うランサムウェアの事例が90%増加した。被害に遭った組織は約5,000に上り、前年の2倍の数であった。また、サイバー犯罪者がジェネレーティブAIを攻撃に利用するなど、ランサムウェア・アズ・ア・サービス(RaaS)が深刻な問題となっている。

これらの詳細は、チェック・ポイント社の「2024年サイバーセキュリティレポート」によるもので、暗い見通しと楽観的な見通しが混在している。サイバー脅威はより巧妙かつ攻撃的になっているが、希望を持つ理由もまだある。一部の主要なサイバー犯罪者は逮捕されており、サイバーセキュリティソリューションは脅威に追いついている。

注目に値する分野のひとつが、ソフトウェア定義型WAN(SD-WAN)である。このテクノロジーは、ネットワーク管理の簡素化、アプリケーションパフォーマンスの向上、運用コストの削減など、企業にさまざまなメリットをもたらすことから、人気が高まっている。SD-WANの普及に伴い、エッジデバイスの利用も拡大しているが、現在では、脅威をもたらす行為者(脅威アクター)がこのエッジデバイスを標的にしている。つまり、ITインフラのセキュリティ確保には、新たなパラダイムの採用が必要である。

SD-WANにおけるセキュリティの必要性

SD-WANは、現代の企業のネットワークインフラを最適化し、従来のWANを強化する画期的な技術である。しかし、企業がSD-WANを採用するにつれ、必然的にサイバー攻撃の対象となる領域が拡大する。SD-WANでは複数の接続を使用するため、ハッカーにとっての攻撃ポイントが増えることになる。チェック・ポイントのサイバーセキュリティレポートでは、攻撃者がサイバー防御を突破する新たな方法を見つけ、ルーターやスイッチなどの広く使用されているデバイスが容易に攻撃対象となっていることが指摘されている。

SD-WANやその他のネットワーク技術の採用に伴う接続の性質により、従来の境界防御はもはや有効ではなくなっている。また、クラウドやハイブリッド環境を利用する組織が増えているが、これらは通常のファイアウォールやその他の従来のセキュリティツールでは保護できない。SD-WANのセキュリティニーズに合わせて、ゼロトラストアーキテクチャを導入し、セキュリティ要件を総合的に解決することが望ましい。

SD-WAN は本質的に安全なものでも、攻撃を受けやすいものでもない。しかし、他のほとんどのテクノロジーと同様に、さまざまな攻撃に悪用される脆弱性がある。管理面の脆弱性により、不正アクセス、データ盗難、設定操作が可能になる可能性がある。また、ハッカーは SD-WAN を利用して特権を拡大し、セキュリティ制御を回避し、サプライチェーン攻撃を組織的に行うことができる。

SD-WANへのセキュリティの統合

セキュリティの脆弱性は、SD-WANのメリットを簡単に損なう可能性がある。そのため、セキュリティ機能を追加したり、エンドツーエンドの暗号化や脅威インテリジェンスなどのサイバー防御機能を統合することが重要である。企業は、ネットワークのセグメント化、セキュリティポリシーの開発、継続的な監視、多要素認証など、複数のセキュリティ機能の実装を伴う階層的なセキュリティ戦略を通じて、SD-WANを安全にすることができる。

さらに、次世代ファイアウォール(NGFW)、セキュアアクセスサービスエッジ(SASE)、侵入検知/防止システム(IDS/IPS)、セキュアウェブゲートウェイ(SWG)などのさまざまなソリューションをSD-WANに統合することも可能である。また、ゼロトラストセキュリティモデル、集中型セキュリティ管理、デバイスを安全にオンボード化するメカニズムを導入することも推奨される。

これらは複雑に聞こえるかもしれないし、多くの組織が精通しているものではないかもしれない。しかし、ほとんどの場合、SD-WANにセキュリティを統合するには、すでにSD-WANとセキュリティ機能を組み合わせたネットワークデバイスやエッジデバイスを選択すればよい。企業は、個別のセキュリティソリューションをSD-WANデバイスに統合することもできるが、SD-WANとセキュリティ機能を巧みに組み合わせたデバイスを導入する方がより便利なオプションである。ここで注目すべきは、大手セキュリティベンダーであるチェック・ポイントが、セキュリティ機能を組み込んだSD-WAN製品を提供していることだ。

SD-WANのメリットを最大限に活用する

世界には約150億台のエッジデバイスが導入されている。これは、あらゆるセキュリティの欠陥や脆弱性を悪用しようと狙っている執拗なサイバー犯罪者にとって、数十億ものサイバー攻撃の標的が存在することを意味する。チェック・ポイントのレポートが示すように、エッジデバイスに対する攻撃の傾向は高まっている。SD-WANが期待されるメリットを実現するには、セキュリティの脅威への対策が不可欠である。

その代わりに、セキュリティ機能を備えた一般的なSD-WANアプライアンスを選ぶことが非常に有効である。高度なトラフィック管理、ダイナミックルーティング、WAN最適化、自動パス選択、ゼロタッチプロビジョニングなどの機能を備えた高度なネットワークアプライアンスは、セキュリティ機能のないルーターと比べてそれほど優れているわけではない。サイバー防御機能が欠如しているために侵害された瞬間、その機器は役に立たなくなる。

企業は、SD-WANの計画と導入にあたり、セキュリティを考慮する必要がある。計画段階では、特にSD-WANの導入によって攻撃対象領域が拡大することに留意し、脅威を慎重に評価する必要がある。脅威の評価後は、明確かつ包括的なセキュリティポリシーを策定し、優れたセキュアなSD-WANソリューションを選択することが重要である。

導入段階では、構成のセキュリティを確保し、既存のセキュリティシステムと統合し、脆弱性を慎重に管理することが重要である。定期的なパッチ適用とアップデートのスケジュールを確立する必要がある。また、最新のセキュリティ修正と最適化機能に対応するため、SD-WANソフトウェアやファームウェアも迅速にアップデートすべきである。

セキュアな最適化

SD-WANとセキュリティは論理的なパートナーである。SD-WANはネットワーク管理を簡素化し、高速化し、アプリケーションのパフォーマンスを向上させ、多様な接続タイプの管理コストを削減する。しかし、SD-WANはまた、新たな、そして未知のサイバー脅威をもたらす。そのため、進化する脅威の状況がネットワークの最適化やアプリケーションのパフォーマンス向上のメリットを相殺しないように、SD-WANにセキュリティを組み込むことが不可欠である。
New regulation intensifies focus on IT risk management and operational resilience

Digital transformation initiatives, for the most part, offer significant advantages—enhancing efficiency, agility, and innovation across the business. However, these initiatives can also introduce new challenges. As IT landscapes and software delivery processes evolve, the risk of inadvertently creating new vulnerabilities increases. Left unaddressed, these gaps can result in cyberattacks, system outages, and network intrusions.

These risks are particularly critical for financial services institutions, which are now under greater scrutiny with the Digital Operational Resilience Act (DORA). This comprehensive regulation applies to all financial institutions in the European Union (EU), as well as third-party providers of information and communication technology (ICT) services to financial entities. Only small firms are exempt from DORA—those with fewer than 10 employees or less than €2 million on their annual turnover and balance sheets.

A comprehensive regulatory reach

DORA addresses a broad range of ICT risks, including incident response, resilience testing, third-party risk management, and information sharing. To achieve compliance, financial institutions must implement robust controls, submit detailed reports, conduct regular penetration tests, and establish effective third-party risk management strategies, all while adhering to data privacy regulations and other requirements. With dozens of specific rules, DORA’s reach is extensive and far-reaching.

The regulation impacts a broad spectrum of financial institutions, including banks, brokers, credit institutions, insurance companies, and payments processors. Moreover, it also applies to all the IT services firms that provide critical functions like cloud hosting, payment processing, data analytics, and other digital services to these financial institutions.

When DORA becomes effective on January 17, 2025, non-compliance with DORA will trigger severe administrative and criminal penalties. For example, a noncompliant third party could face daily fines of 1% of its previous year’s average daily turnover for up to six months. Penalties will be determined by the severity and duration of the noncompliance, whether it was intentional, and the organization’s willingness to cooperate with DORA authorities. EU member states could also impose additional criminal penalties in accordance with their national laws.

Proactive preparation with AI-powered solutions

With DORA’s deadline quickly approaching, preparing for DORA is critical. Organizations need solutions that not only ensure compliance but also provide cost-effective, scalable and confidence-building approaches to address potential risk scenarios.

For example, the BMC Helix platform is a comprehensive, AI-powered solution designed to align with DORA’s requirements. With integrated capabilities like service management, operations management and monitoring, mainframe management, and business process automation tools, BMC Helix empowers financial institutions to ensure compliance with DORA’s requirements for governance, visibility, risk management, business continuity, and incident management.

One notable tool, BMC HelixGPT, uses a large language model (LLM) that drives a suite of AI-powered software agents. These agents perform critical services like discovery service mapping, capacity optimization, and more, acting as a copilot for teams managing DORA compliance. By integrating with other data platforms like Snowflake, BMC HelixGPT enables insightful data analysis, ensuring relevant information is readily and timely accessible. In addition, BMC Helix dashboards provide DORA-focused insights and generate reports tailored to DORA-specific requirements.

Ultimately, BMC Helix not only helps reduce vulnerabilities—minimizing the risks of cyberattacks, data breaches, and system outages—but also supports the goal of DORA to increase operational resilience.

The renewed priority of mainframe operational resilience

For financial services, mainframe operational resilience demands a new approach. These systems are crucial to DORA’s mandate, yet many organizations lag in disaster recovery, relying on outdated strategies. Regulators now require immutable data—physically and logically separated—to ensure resilience. BMC AMI provides solutions for Service Awareness, Risk Management, Business Continuity, Incident Management, and Governance, ensuring mainframes remain secure, resilient, and aligned with business goals. Operational resilience goes beyond compliance; it protects the organization’s core.

But remember: DORA’s enforcement takes effect in January, so the time to act is now. By investing in the right solutions, your institution can enhance its resilience, avoid costly penalties, and secure a future where operational disruptions are minimized, and business objectives and goals are met with greater confidence.

Learn more about DORA and how BMC can help. Visit here for more information or contact BMC.
4 steps toward integrating genAI into DevSecOps processes
A hallmark of DevSecOps is that security is a shared responsibility. Generative artificial intelligence (genAI) can reinforce that principle by improving communication and collaboration. What’s more, by substituting automation for certain manual operations, genAI can significantly reduce human error and heighten product reliability.

Accelerating vulnerability remediation with genAI

Although the responsibilities of developers, security professionals, and operations teams overlap, their communications are often hampered by the inability to quickly grasp esoteric terms that are specific to each discipline. GenAI can act as a liaison, translating security concepts into language DevOps teams can understand and vice versa. When everyone is on the same page, collaboration is more effective. With less time lost due to confusion or misunderstandings, DevSecOps teams can devote more of their attention to strategic tasks such as vulnerability remediation.

GenAI offers significant benefits when fixing vulnerabilities. The technology can review code more thoroughly than humans can, identifying patterns that might not seem obvious. For example, a typical human reaction upon spotting a vulnerability is to comb the internet for relevant information, analyze findings to understand the potential impact, and use the insights gained to prioritize remediation efforts. GenAI can do that job much faster, and it can also find and evaluate vendor fixes and even generate scripts to improve on them.

Cybercriminals are enthusiastically using ChatGPT and similar tools to turn vulnerabilities into exploits much faster. It’s critical for DevSecOps teams to apply similar methods and protect their systems against evolving threats.

4 steps to genAI integration in DevSecOps

Organizations that are ready to apply genAI capabilities to vulnerability remediation in their DevSecOps processes can start developing plans according to four basic steps:

Assess the current DevSecOps framework. While the target areas may vary from one business to the next, genAI typically has the greatest impact on communication, collaboration, code review, and vulnerability management.

Incorporate genAI into existing workflows. Communication should come first, because without mutual understanding, collaboration may be weak. Next, genAI tools should be integrated into vulnerability detection, prioritization, and remediation processes.

Train genAI models on internal data. GenAI systems must be trained on trusted internal sources to maintain data security and privacy. Third-party systems that have the capability of exposing sensitive company information to the internet should be avoided.

Implement genAI–driven automation. GenAI can create and deploy scripts for remediating vulnerabilities, easing the burden on DevSecOps team members. Automated analysis of past actions and effective solutions can be invaluable aids in improving genAI recommendations for vulnerability fixes.

Learn more about ways to accelerate developer speed, while delivering reliability and security.

Proactive security and accelerated processes

Taking a preemptive approach to vulnerability remediation is a surefire way to strengthen security and reliability. BMC Helix offers IT, security, and developer teams control over sources and model training, as well as highly useful histories of customers, events, and procedures relative to the DevSecOps environment. Automation reduces the likelihood of human error, and increased efficiency alleviates pressure on overburdened staff. BMC Helix offers an easily integrated solution toward future proofing any organization’s security posture.

Discover how generative AI is bringing DevSecOps to life. Visit here for more information or contact BMC.
Composite AI: The trifecta that is transforming AIOps
When it comes to the different types of artificial intelligence (AI), 1+1+1 can equal more than three. Composite AI combines causal, predictive, and generative AI to supercharge AIOps, reducing mean time to resolution (MTTR) from hours or days to minutes. Composite AI provides explanations of root causes in plain language and often automatically fixes issues before they grow into giant headaches for IT.

First, a brief description of these three types of AI:

Causal AI analyzes data to infer the root causes of events. For example, if a company’s e-commerce website is taking too long to process customer transactions, a causal AI model determines the root cause (or causes) of the delay, such as a misconfigured load balancer.

Predictive AI can identify potential issues before they become problems, such as identifying a load balancer misconfiguration that, while it may not affect transaction processing time during normal loads, will result in long delays during a big event such as Black Friday.

Generative AI (genAI) is based on large language models (LLMs) that enable the technology to understand text and generate explanations for IT in plain language. GenAI can even create working code.

The result of this combination is that instead of working with myriad disconnected tools that only provide insight into their own specific silos — applications, networking, endpoints, and so on — composite AI enables AIOps to provide holistic visibility across the entire environment. So, when an application goes down, instead of having to compare different reports from different tools and then parse out the root cause on your own, AIOps analyzes data across these different functions to provide IT with a succinct explanation in natural language that any IT admin can readily understand.

Plus, composite AI can do more than just point to the root cause; it can also provide actions and even the exact code that will address the issue. Even better, AIOps can learn from past events to predict problems before they occur and, in many cases, automatically fix them without any human intervention at all.

Increase uptime and reduce MTTR

The BMC Helix platform uses composite AI to provide exactly these benefits to IT and does so in a safe and secure way. BMC uses pre-trained LLMs to customize training for IT operations and service management (ServiceOps) domains. These models draw on BMC’s extensive expertise and are trained on organizational IT data and are far less susceptible to “hallucinations” in AI terms. The results are composite AI solutions that can identify, address, and explain root causes and emerging future problems accurately.

AI trained on biased data may produce unreliable results. Building on this key understanding, BMC Helix continually learns from customer data — topology, events, metrics, incidents, tickets, and more — to provide an ever more insightful and predictive view of the environment. This customer data, however, remains on customer systems.

“AIOps brings in a neutral, well-informed, well-educated expert that can learn from your data and past experiences to enable IT to fix issues faster — often before users ever notice a problem,” said Margaret Lee, senior vice president and general manager of Digital Service and Operations Management, BMC Software.

In the end, composite AI enables AIOps to provide even more insightful predictions, more accurate root cause analysis, and broader, higher resolution observability of the environment.

Ultimately, what matters most is composite AI enables IT to provide exponentially better performance and greater uptime to customers.

Address your IT service delivery challenges with the most effective composite AI solution. Visit here for more information or contact BMC.

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