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November 3, 2024

AI and Cybersecurity: Predictions for 2025

Discover the role of AI in shaping cybersecurity predictions for 2025 and how organizations can prepare for emerging threats.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
The Darktrace Community
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03
Nov 2024

Introduction: AI cybersecurity predictions for 2025

Each year, Darktrace's AI and cybersecurity experts reflect on the events of the past 12 months and predict the trends we expect to shape the cybersecurity landscape in the year ahead. In 2024, we predicted that the global elections, fast-moving AI innovations, and increasingly cloud-based IT environments would be key factors shaping the cyber threat landscape.

Looking ahead to 2025, we expect the total addressable market of cybercrime to expand as attackers add more tactics to their toolkits. Threat actors will continue to take advantage of the volatile geopolitical environment and cybersecurity challenges will increasingly move to new frontiers like space. When it comes to AI, we anticipate the innovation in AI agents in 2024 to pave the way for the rise of multi-agent systems in 2025, creating new challenges and opportunities for cybersecurity professionals and attackers alike.

Here are ten trends to watch for in 2025:

1. The overall Total Addressable Market (TAM) of cybercrime gets bigger

Cybercrime is a global business, and an increasingly lucrative one, scaling through the adoption of AI and cybercrime-as-a-service. Annual revenue from cybercrime is already estimated to be over $8 trillion, which we’ve found is almost 5x greater than the revenue of the Magnificent Seven stocks. There are a few key factors driving this growth.

The ongoing growth of devices and systems means that existing malware families will continue to be successful. As of October 2024, it’s estimated that more than 5.52 billion people (~67%) have access to the internet and sources estimate 18.8 billion connected devices will be online by the end of 2024. The increasing adoption of AI is poised to drive even more interconnected systems as well as new data centers and infrastructure globally.

At the same time, more sophisticated capabilities are available for low-level attackers – we’ve already seen the trickle-down economic benefits of living off the land, edge infrastructure exploitation, and identity-focused exploitation. The availability of Ransomware-as-a-Service (RaaS) and Malware-as-a-Service (MaaS) make more advanced tactics the norm. The subscription income that these groups can generate enables more adversarial innovation, so attacks are getting faster and more effective with even bigger financial ramifications.

While there has also been an increasing trend in the last year of improved cross-border law enforcement, the efficacy of these efforts remains to be seen as cybercriminal gangs are also getting more resilient and professionalized. They are building better back-up systems and infrastructure as well as more multi-national networks and supply chains.

2. Security teams need to prepare for the rise of AI agents and multi-agent systems

Throughout 2024, we’ve seen major announcements about advancements in AI agents from the likes of OpenAI, Microsoft, Salesforce, and more. In 2025, we’ll see increasing innovation in and adoption of AI agents as well as the emergence of multi-agent systems (or “agent swarms”), where groups of autonomous agents work together to tackle complex tasks.

The rise of AI agents and multi-agent systems will introduce new challenges in cybersecurity, including new attack vectors and vulnerabilities. Security teams need to think about how to protect these systems to prevent data poisoning, prompt injection, or social engineering attacks.

One benefit of multi-agent systems is that agents can autonomously communicate, collaborate, and interact. However without clear and distinct boundaries and explicit permissions, this can also pose a major data privacy risk and avenue for manipulation. These issues cannot be addressed by traditional application testing alone. We must ensure these systems are secure by design, where robust protective mechanisms and data guardrails are built into the foundations.

3. Threat actors will be the earliest adopters of AI agents and multi-agent systems

We’ve already seen how quickly threat actors have been able to adopt generative AI for tasks like email phishing and reconnaissance. The next frontier for threat actors will be AI agents and multi-agent systems that are specialized in autonomous tasks like surveillance, initial access brokering, privilege escalation, vulnerability exploitation, data summarization for smart exfiltration, and more. Because they have no concern for safe, secure, accurate, and responsible use, adversaries will adopt these systems faster than cyber defenders.

We could also start to see use cases emerge for multi-agent systems in cyber defense – with potential for early use cases in incident response, application testing, and vulnerability discovery. On the whole, security teams will be slower to adopt these systems than adversaries because of the need to put in place proper security guardrails and build trust over time.

4. There is heightened supply chain risk for Large Language Models (LLMs)

Training LLMs requires a lot of data, and many experts have warned that world is running out of quality data for that training. As a result, there will be an increasing reliance on synthetic data, which can introduce new issues of accuracy and efficacy. Moreover, data supply chain risks will be an Achilles heel for organizations, with the potential interjection of vulnerabilities through the data and machine learning providers that they rely on. Poisoning one data set could have huge trickle-down impacts across many different systems. Data security will be paramount in 2025.

5. The race to identify software vulnerabilities intensifies

The time it takes for threat actors to exploit newly published CVEs is getting shorter, giving defenders an even smaller window to apply patches and remediations. A 2024 report from Cloudflare found that threat actors quickly weaponized proof of concept exploits in attacks as quickly as 22 minutes after the exploits were made public.

At the same time, 2024 also saw the first reports from researchers across academia and the tech industry using AI for vulnerability discovery in real-world code. With threat actors getting faster at exploiting vulnerabilities, defenders will need to use AI to identify vulnerabilities in their software stack and to help identify and prioritize remediations and patches.

6. Insider threat risks will force organizations to evolve zero trust strategies

In 2025, an increasingly volatile geopolitical situation and the intensity of the AI race will make insider threats an even bigger risk for businesses, forcing organizations to expand zero-trust strategies. The traditional zero-trust model provides protection from external threats to an organization’s network by requiring continuous verification of the devices and users attempting to access critical business systems, services, and information from multiple sources. However, as we have seen in the more recent Jack Teixeira case, malicious insiders can still do significant damage to an organization within their approved and authenticated boundary.

To circumvent the remaining security gaps in a zero-trust architecture and mitigate increasing risk of insider threats, organizations will need to integrate a behavioral understanding dimension to their zero-trust approaches. The zero-trust best practice of “never trust, always verify” needs to evolve to become “never trust, always verify, and continuously monitor.”

7. Identity remains an expensive problem for businesses

2024 saw some of the biggest and costliest attacks – all because the attacker had access to compromised credentials. Essentially, they had the key to the front door. Businesses still struggle with identity and access management (IAM), and it’s getting more complex now that we’re in the middle of a massive Software-as-a-Service (SaaS) migration driven by increasing rates of AI and cloud use across businesses.

This challenge is going to be exacerbated in 2025 by a few global and business factors. First, there is an increasing push for digital identities, such as the rollout of the EU Digital Identity Framework that is underway, which could introduce additional attack vectors. As they scale, businesses are turning more and more to centralized identity and access solutions with decentralized infrastructure and relying on SaaS and application-native security.

8. Increasing vulnerabilities at the edge

During the COVID-19 pandemic, many organizations had to stand-up remote access solutions quickly – in a matter of days or weeks – without the high level of due diligence that they require to be fully secured. In 2025, we expect to see continued fall-out as these quickly spun-up solutions start to present genuine vulnerability to businesses. We’ve already seen this start to play out in 2024 with the mass-exploitation of internet-edge devices like firewalls and VPN gateway products.

By July 2024, Darktrace’s threat research team observed that the most widely exploited edge infrastructure devices were those related to Ivanti Connect Secure, JetBrains TeamCity, FortiClient Enterprise Management Server, and Palo Alto Networks PAN-OS. Across the industry, we’ve already seen many zero days and vulnerabilities exploiting these internet-connected devices, which provide inroads into the network and store/cache credentials and passwords of other users that are highly valuable for threat actors.

9. Hacking Operational Technology (OT) gets easier

Hacking OT is notoriously complex – causing damage requires an intimate knowledge of the specific systems being targeted and historically was the reserve of nation states. But as OT has become more reliant and integrated with IT systems, attackers have stumbled on ways to cause disruption without having to rely on the sophisticated attack-craft normally associated with nation-state groups. That’s why some of the most disruptive attacks of the last year have come from hacktivist and financially-motivated criminal gangs – such as the hijacking of internet-exposed Programmable Logic Controllers (PLCs) by anti-Israel hacking groups and ransomware attacks resulting in the cancellation of hospital operations.  

In 2025, we expect to see an increase in cyber-physical disruption caused by threat groups motivated by political ideology or financial gain, bringing the OT threat landscape closer in complexity and scale to that of the IT landscape. The sectors most at risk are those with a strong reliance on IoT sensors, including healthcare, transportation, and manufacturing sectors.

10. Securing space infrastructure and systems becomes a critical imperative

The global space industry is growing at an incredibly fast pace, and 2025 is on track to be another record-breaking year for spaceflight with major missions and test flights planned by NASA, ESA, CNSA as well as the expected launch of the first commercial space station from Vast and programs from Blue Origin, Amazon and more. Research from Analysis Mason suggests that 38,000 additional satellites will be built and launched by 2033 and the global space industry revenue will reach $1.7 trillion by 2032. Space has also been identified as a focus area for the incoming US administration.

In 2025, we expect to see new levels of tension emerge as private and public infrastructure increasingly intersect in space, shining a light on the lack of agreed upon cyber norms and the increasing challenge of protecting complex and remote space systems against modern cyber threats.  Historically focused on securing earth-bound networks and environments, the space industry will face challenges as post-orbit threats rise, with satellites moving up the target list.

The EU’s NIS2 Directive now recognizes the space sector as an essential entity that is subject to its most strict cybersecurity requirements. Will other jurisdictions follow suit? We expect global debates about cyber vulnerabilities in space to come to the forefront as we become more reliant on space-based technology.

Conclusion: Preparing for the future

Whatever 2025 brings, Darktrace is committed to providing robust cybersecurity leadership and solutions to enterprises around the world. Our team of subject matter experts will continue to monitor emerging threat trends, advising both our customers and our product development teams.

And for day-to-day security, our multi-layered AI cybersecurity platform can protect against all types of threats, whether they are known, unknown, entirely novel, or powered by AI. It accomplishes this by learning what is normal for your unique organization, therefore identifying unusual and suspicious behavior at machine speed, regardless of existing rules and signatures. In this way, organizations with Darktrace can be ready for any developments in the cybersecurity threat landscape that the new year may bring.

Discover more about Darktrace's predictions on the AI and cybersecurity landscape for 2025 by watching the full recorded webinar here.

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
The Darktrace Community

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June 1, 2026

効率化の裏にあるリスク:AI導入が製造現場にもたらす見えない脆弱性

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AIエージェントが製造業に与える影響

製造業界のセキュリティチームやIT担当者は、生産を守り、稼働時間を維持し、重要資産を保護するという絶え間ないプレッシャー下にあります。そしてAIは非常に大きなチャンスとともに、新たなサイバーリスクももたらしています。製造業全体で、AIはワークフローや意思決定に組み込まれつつあり、自律型AIエージェントが従業員やシステムに代わって行動する場面が増えています。

エージェント型システムは独立して行動できるため強力ですが、その同じ自律性がサイバーリスク、運用上のリスクも生み出します。エージェントは広範な権限を持ち、複雑なタスクの実行、意思決定、ツールや外部システムとのやり取りを、ほとんどまたは全く人間の介入なしに行うことができます。

あらかじめ定義されたタスクを実行する従来のAIモデルとは異なり、AIエージェントは高度なテクニックを使用して人間の意思決定プロセスを模倣することにより、新たな課題に動的に適応し、また自らの判断に基づいて意思決定し、アクションを実行します。彼らは業務の上では従業員のように見えますが、人間が持つ判断力、倫理観、または行動の結果に対する恐れが欠けています。これは、サイバー犯罪者によって簡単に操られる可能性があることを意味しており、OTネットワーク全体に埋め込まれたAIエージェントは、データ漏洩をはるかに超える脅威を生み出します。たとえば、BMWでは、AI は溶接プロセスのエラーの発生を識別するのに使われています。同社のスパータンバーグ(米サウスカロライナ州)の工場では、すべてのSUVフレーム上の300-400個のスタッドの溶接をAIが監視し、スタッドの配置間違いや欠陥を検知し直ちに修正します。このAIシステムが破損すれば壊滅的な品質管理問題につながる恐れがあります。

製造全体にエージェント型AIシステムを導入することについて多くのセキュリティチームはさまざまな懸念を示しています。ダークトレースの行ったAIサイバーセキュリティの現状調査では、製造業のセキュリティプロフェッショナルの78%が従業員によるAIエージェントの利用に懸念を抱いており、これは彼らの最も大きな危惧でした。それに続く問題点が従業員によるCopilotやChatGPT等の生成AIツールの使用であり、製造業のセキュリティプロフェッショナルの76%が懸念を抱いていました。これらのツールがますます多くのビジネスデータやプロセスにアクセスし、組織内でより多くの自律性を持つようになるにつれ、エージェントのアクティビティがほとんど可視化されていない現在、セキュリティチームにおいては機密データの露出(60%)や偶発的なポリシーおよび規制違反(59%)への懸念が高まっています。

外部からのAIによる脅威も急激に進化

製造業を変革しているのと同じAIの能力が、サイバー攻撃の形も変貌させています。

AIにより攻撃者は偵察を自動化し、標的をより高度に絞り込み、リアルタイムで適応できるようになっています。かつては人手による作業と時間を要していたことが、今では継続的かつ大規模に実行できるようになりました。そして、製造業はすでにその影響を実感しています。当社が調査した製造業のセキュリティプロフェッショナルの76%は、すでにAIを活用した脅威の影響を受けており、90%がAIによってソーシャルエンジニアリング攻撃の成功率が高まっていると回答しています。

また、攻撃のテクニック自体も進化しています。製造業界全体で、AIを利用した攻撃の経路の多様化に対する懸念が高まっています。特にリアルタイムで進化する適応型マルウェアについて、調査対象の製造業のセキュリティプロフェッショナルの半数近く(49%)が懸念しており、これは全産業の平均よりも9%高い数値です。AIを使った適応型マルウェアに続くその他の懸念には次が含まれます:

  • 自動化された脆弱性スキャンとエクスプロイトチェイニング(48%):Anthropicの新しいMythos AIモデルにより脆弱性探索が深刻化する中で、この問題は一層差し迫ったものとなっています。
  • 超パーソナライズされたフィッシングキャンペーン(46%):フィッシングは依然としてハッカーの主力兵器の1つであり、AIによってフィッシングメールはより説得力が高く検知困難なものとなり、その効果は増幅されました。

これは単に攻撃の量の増加だけでなく、攻撃の展開につれて静的な防御が対応できるよりも速く進化する脅威への変化なのです。

こうした認識が高まっているにもかかわらず、製造業の多くはまだこの変化に対応する準備ができていません。半数以上(51%)がAI駆動の脅威への準備が十分にできていないと回答し、AIの導入を管理する正式なポリシーを持っている組織はわずか37%でした。  

可視性、コンテキスト、およびガードレールを通じてAIのセキュリティを確保

これらの問題に対処するためにAIイノベーションを遅らせる必要はありません。それには、AIと同じスピードと規模で動作できる、これまでとは異なるアプローチのセキュリティが必要です。具体的には、製造業がAIの力を活用する上で、次の3つの優先課題が浮上しています。

可視性はすべての土台  

AIがどこで使用されているか、何にアクセスできるか、そしてITおよびOT環境にわたってどのように動作するかを理解する必要があります。それがなければ、リスクを測定したり管理したりすることはできません。ダークトレースの調査において、製造業のセキュリティプロフェッショナルの91%が、AIを信頼する前に、それがどのように意思決定を行うかを理解する必要があると回答したのは当然のことです。OT環境においてこのことはさらに重要です。稼働の中断は安全や環境、財務、および評判に大きな影響を及ぼすからです。

可視性をアクションにつなげるにはコンテキストが必要  

AIによって形作られる環境において、正常とされる挙動は絶えず変化します。つまり、脅威を検知するにはビヘイビアベースのアプローチが必要なのです。組織全体で生活パターンを理解し、わずかな逸脱をリアルタイムに検知すること- これは従来のセキュリティとリスク管理に対するアプローチからの根本的な変化です。

エージェントからの露出を防ぐガードレール  

AIシステムがより大きな責任を担うようになるなかで、組織はAIが何をできるか、そしていつ独立して行動できるかについて、明確な境界を設ける必要があります。これらのコントロールは何かがあってから適用されるのではなく、システム自体に組み込んでおかなければなりません。  

製造業のITおよびOT環境におけるAIエージェントのセキュリティ

エージェント型AIの出現は製造業を変革し、次世代のオペレーションを支える一方で、脅威ランドスケープも一変させています。これは単なる脅威の増加ではなく、自律型システムへの移行、挙動の絶え間ない変化、そしてマシンスピードで進行するリスクです。AIを活用しつつリスクを管理するという課題に取り組む組織にとって、可視性、コンテキスト、ガードレールはセキュリティの基盤となります。

Darktraceはこの基盤を実現することにより、製造業の安全なAIアプローチ構築を支援します。ITおよびOT環境全体を可視化し、異常なアクティビティに対するリアルタイムの検知および対応を提供することにより、従業員が使用するプロンプトや構築するエージェントから、それらのエージェントの環境全体での動作に至るまで、AIアクティビティの理解を可能にします。これにより、AIの導入を拡大する製造業はコントロールを犠牲にすることなくイノベーションの基盤を構築することができます。

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Oakley Cox
Director of Product

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June 1, 2026

Defend What You Trust: Stories from the Front Lines of Modern Cyber Defense

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Modern attacks don’t always announce themselves, follow obvious patterns, or rely on known malware. Often, they move quietly inside trusted systems, authenticated sessions, and everyday behavior.

They don’t break in. They blend in.

That’s why an AI-powered defense is essential. It turns invisible signals into actionable insights at a scale neither analysts nor traditional tools can achieve alone.

Confidence is creating risk

One of the most dangerous assumptions in cybersecurity today is that strong controls equal strong protection.

Multi-factor authentication (MFA), for example, is widely viewed as a foundational safeguard. But as the CISO for a professional sports organization explains, that confidence can be misplaced. “A lot of organizations assume that once you have MFA, those accounts are safe. That’s not true.”

In one instance, his team identified a sophisticated attack where a threat actor bypassed MFA entirely, not by breaking it, but by going around it. A user’s authenticated session was hijacked and re-used, allowing the attacker to impersonate them without triggering traditional controls.

“Darktrace picked up that a session had been re-injected by the hacker, and we were able to block it right away,” he explains.

Attackers anticipate what we miss

Even well-trained users can become entry points.

“An email bypassed our existing security tools,” shares the VP of IT at a U.S.-based risk management services provider.  “The user missed one signal and entered their credentials into a malicious site. That’s what the bad guys count on.”

The organization responded quickly, but not before damage was done. Crucially, this occurred while Darktrace was in “watch mode,” before autonomous response was fully enabled. “Darktrace would have seen that and shut it down immediately,” he notes.

Mistakes and oversights like misconfigurations, forgotten machines, and missed patches can create serious vulnerabilities.

The CIO of a utility services organization shares an instance when Darktrace detected a breach to a client’s network via their ZTNA VPN due to misconfigured MFA. “Darktrace alerted us and autonomously blocked the scanning, preventing what could have been a ransomware-type incident.”  

The most dangerous threats are already inside

The Head of Security at a global business services provider knows firsthand how blind spots can persist inside environments. His team uncovered evidence of dormant ransomware artifacts sitting unnoticed within a company’s environment ¬¬– long before modern detection was in place.

“During a routine file transfer, Darktrace flagged the suspicious activity, identified the ransomware, and immediately quarantined the server,” he recalls.  While the attack was never executed, the implication was significant: the risk existed long before it was finally detected.

Cyber threats are also successful because they take advantage of normal human behavior, exploiting moments of cognitive overload, urgency, and trust.

The Executive Director of IT and Business Applications at a pharmaceutical lab describes the time Darktrace flagged an employee logging into Microsoft 365 from Singapore, despite him being physically located in the U.S. Darktrace immediately cut off his access and within minutes revealed that the employee’s son was using a VPN to play a video game.

While the threat was benign, it demonstrated the strength of AI to use contextual information to detect threats other tools miss. The information also saved security analysts hours of investigation and minimized downtime for the employee. “That level of precision and speed isn’t just convenient, it’s game changing.”

“Unusual” behavior is the new red flag

Detecting modern threats requires an understanding of what “normal” looks like and recognizing when something subtly deviates.

One security leader  at an AI technology enterprise described a scenario in which an employee connected to a proxy service in China. The service itself was legitimate, and although traditional tools didn’t flag it, the behavior was unusual for that user specifically.

“That’s what Darktrace picked up on. The activity turned out to be benign, but without visibility into behavioral deviations, it could just as easily have been something more serious.”

AI shifts defense from reaction to anticipation

These stories point to a fundamental shift by cyber attackers, both tactically and strategically. Because traditional security tools were built to detect what’s already known, modern attacks are often:

  • Credential-based, not malware-based
  • Behavioral, not signature-based
  • Subtle, not overt

They may operate within the boundaries of what appears normal, exploiting what organizations trust, not what they block:

  • Trusted sessions
  • Legitimate services
  • Human error

This is where AI is changing the equation. Rather than relying on predefined rules or known threat signatures, AI can:

  • Establish a baseline of normal behavior
  • Detect subtle anomalies in real time
  • Act autonomously to contain potential threats

Resilience, not perfection, is the new security standard

As these frontline experiences show, the organizations that lead are those that move beyond reactive defense and embrace AI as a core part of their strategy.

It eliminates the blind spots and uncertainty, says the CISO of a professional sports organization. “If you lack visibility, you’re not managing risk, you’re assuming it. AI gives you the actionable insights needed to turn uncertainty into control.”

And it provides the speed and agility that are vital when seconds matter, says the Executive Director of IT and Business Applications. “When Darktrace alerted us at 3:00 am to a ransomware attack, it had already quarantined the affected systems, blocked the attacker’s access, and provided us with the critical details and time needed to investigate. That action likely saved us hundreds of thousands, if not millions, of dollars.”

The modern SOC has become a cornerstone of enterprise resilience, responsible for protecting data and operational continuity while enabling digital growth and innovation. For today’s security professional, that means success is no longer measured by what they keep out, but by what they protect: revenue, reputation, and trust.

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