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September 13, 2023

How Darktrace Stopped Akira Ransomware

Learn how Darktrace is uniquely placed to identify and contain the novel Akira ransomware strain, first observed in March 2023.
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
Manoel Kadja
Cyber Analyst
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13
Sep 2023

Introduction to Akira Ransomware

In the face of a seemingly never-ending production line of novel ransomware strains, security teams across the threat landscape are continuing to see a myriad of new variants and groups targeting their networks. Naturally, new strains and threat groups present unique challenges to organizations. The use of previously unseen tactics, techniques, and procedures (TTPs) means that threat actors can often completely bypass traditional rule and signature-based security solutions, thus rendering an organization’s digital environment vulnerable to attack.

What is Akira Ransomware?

One such example of a novel ransomware family is Akira, which was first observed in the wild in March 2023. Much like many other strains, Akira is known to target corporate networks worldwide, encrypting sensitive files and demanding huge sums of money to retrieve the data and stop it from being posted online [1].

Key characteristics of Akira Ransomware

  • Targeted Attacks: Focuses on specific industries and organizations, often targeting those with valuable data.
  • Double Extortion Tactics: Employs double extortion by encrypting data and threatening to release it publicly if the ransom is not paid.
  • Advanced Encryption: Utilizes sophisticated encryption algorithms to ensure that data recovery is impossible without the decryption key.
  • Custom Ransom Notes: Delivers personalized ransom notes tailored to the victim, often containing detailed instructions and specific payment demands.
  • Stealth Techniques: Uses advanced evasion techniques to avoid detection by security tools and to remain undetected for extended periods.
  • Fast Encryption Process: Known for its rapid encryption process, minimizing the time window for detection and response by the victim.
  • Frequent Updates: Regularly updates its malware to bypass the latest security defenses and to improve its effectiveness.
  • Professional Communication: Maintains professional and often polite communication with victims to facilitate ransom payments and decryption.

Darktrace AI capabilities detect Akira Ransomware

In late May 2023, Darktrace observed multiple instances of Akira ransomware affecting networks across its customer base. Thanks to its anomaly-based approach to threat detection, Darktrace successfully identified the novel ransomware attacks and provided full visibility over the cyber kill chain, from the initial compromise to the eventual file encryptions and ransom notes. In cases where Darktrace was enabled in autonomous response mode, these attacks were mitigated the early stages of the attack, thus minimizing any disruption or damage to customer networks.

Initial access and privileged escalation

Methods used by Akira ransomware for privileged escalation

The Akira ransomware group typically uses spear-phishing campaigns containing malicious downloads or links as their primary initial access vector; however, they have also been known to use Remote Desktop Protocol (RDP) brute-force attacks to access target networks [2].

While Darktrace did observe the early access activities that are detailed below, it is very likely that the actual initial intrusion happened prior to this, through targeted phishing attacks that fell outside of Darktrace’s purview. The first indicators of compromise (IoCs) that Darktrace observed on customer networks affected by Darktrace were typically unusual RDP sessions, and the use of compromised administrative credentials.

Darktrace detection of initial access and priviledged escalation

On one Darktrace customer’s network (customer A), Darktrace identified a highly privileged credential being used for the first time on an internal server on May 21, 2023. Around a week later, this server was observed establishing RDP connections with multiple internal destination devices via port 3389. Further investigation carried out by the customer revealed that this credential had indeed been compromised. On May 30, Darktrace detected another device scanning internal devices and repeatedly failing to authenticate via Kerberos.

As the customer had integrated Darktrace with Microsoft Defender, their security team received additional cyber threat intelligence from Microsoft which, coupled with the anomaly alerts provided by Darktrace, helped to further contextualize these anomalous events. One specific detail gleaned from this integration was that the anomalous scanning activity and failed authentication attempts were carried out using the compromised administrative credentials mentioned earlier.

By integrating Microsoft Defender with Darktrace, customers can efficiently close security gaps across their digital infrastructure. While Darktrace understands customer environments and provides valuable network-level insights, by integrating with Microsoft Defender, customers can further enrich these insights with endpoint-specific information and activity.

In another customer’s network (customer B), Darktrace detected a device, later observed writing a ransom note, receiving an unusual RDP connection from another internal device. The RDP cookie used during this activity was an administrative RDP cookie that appeared to have been compromised. This device was also observed making multiple connections to the domain, api.playanext[.]com, and using the user agent , AnyDesk/7.1.11, indicating the use of the AnyDesk remote desktop service.

Although this external domain does not appear directly related to Akira ransomware, open-source intelligence (OSINT) found associations with multiple malicious files, and it appeared to be associated with the AnyDesk user agent, AnyDesk/6.0.1 [3]. The connections to this endpoint likely represented the malicious use of AnyDesk to remotely control the customer’s device, rather than Akira command-and-control (C2) infrastructure or payloads. Alternatively, it could be indicative of a spoofing attempt in which the threat actor is attempting to masquerade as legitimate remote desktop service to remain undetected by security tools.

Around the same time, Darktrace observed many devices on customer B’s network making anomalous internal RDP connections and authenticating via Kerberos, NTLM, or SMB using the same administrative credential. These devices were later confirmed to be affected by Akira Ransomware.

Figure 1 shows how Darktrace detected one of those internal devices failing to login via SMB multiple times with a certain credential (indication of a possible SMB/NTLM brute force), before successfully accessing other internal devices via SMB, NTLM and RDP using the likely compromised administrative credential mentioned earlier.

Figure 1: Model Breach Event Log indicating unusual SMB, NTLM and RDP activity with different credentials detected which led to the Darktrace model breaches, "Unusual Admin RDP Session” and “Successful Admin Brute-Force Activity”.

Darktrace models observed for initial access and privilege escalation:

  • Device / Anomalous RDP Followed By Multiple Model Breaches
  • Anomalous Connection / Unusual Admin RDP Session
  • New Admin Credentials on Server
  • Possible SMB/NTLM Brute Force Indicator
  • Unusual Activity / Successful Admin Brute-Force Activity

Internal Reconnaissance and Lateral Movement

The next step Darktrace observed during Akira Ransomware attacks across the customer was internal reconnaissance and lateral movement.

How Akira Ransomware conducts internal reconnaissance

In another customer’s environment (customer C), after authenticating via NTLM using a compromised credential, a domain controller was observed accessing a large amount of SMB shares it had never previously accessed. Darktrace understood that this SMB activity represented a deviation in the device’s expected behavior and recognized that it could be indicative of SMB enumeration. Darktrace observed the device making at least 196 connections to 34 unique internal IPs via port 445. SMB actions read, write, and delete were observed during those connections. This domain controller was also one of many devices on the customer’s network that was received incoming connections from an external endpoint over port 3389 using the RDP protocol, indicating that the devices were likely being remotely controlled from outside the network. While there were no direct OSINT links with this endpoint and Akira ransomware, the domain controller in question was later confirmed to be compromised and played a key role in this phase of the attack.

Moreover, this represents the second IoC that Darktrace observed that had no obvious connection to Akira, likely indicating that Akira actors are establishing entirely new infrastructure to carry out their attacks, or even utilizing newly compromised legitimate infrastructure. As Darktrace adopts an anomaly-based approach to threat detection, it can recognize suspicious activity indicative of an emerging ransomware attack based on its unusualness, rather than having to rely on previously observed IoCs and lists of ‘known-bads’.

Darktrace further observed a flurry of activity related to lateral movement around this time, primarily via SMB writes of suspicious files to other internal destinations. One particular device on customer C’s network was detected transferring multiple executable (.exe) and script files to other internal devices via SMB.

Darktrace recognized that these transfers represented a deviation from the device’s normal SMB activity and may have indicated threat actors were attempting to compromise additional devices via the transfer of malicious software.

Figure 2: Advanced Search results showing 20 files associated with suspicious SMB write activity, amongst them executable files and dynamic link libraries (DLLs).

Darktrace DETECT models observed for internal reconnaissance and lateral movement:

  • Device / RDP Scan
  • Anomalous Connection / SMB Enumeration
  • Anomalous Connection / Possible Share Enumeration Activity
  • Scanning of Multiple Devices (Cyber AI Analyst Incident)
  • Device / Possible SMB/NTLM Reconnaissance
  • Compliance / Incoming Remote Desktop
  • Compliance / Outgoing NTLM Request from DC
  • Unusual Activity / Internal Data Transfer
  • Security Integration / Lateral Movement and Integration Detection
  • Device / Anomalous SMB Followed By Multiple Model Breaches

Ransomware deployment

In the final phase of Akira ransomware attacks detected on Darktrace customer networks, Darktrace identified the file extension “.akira” being added after encryption to a variety of files on the affected network shares, as well as a ransom note titled “akira_readme.txt” being dropped on affected devices.

On customer A’s network, after nearly 9,000 login failures and 2,000 internal connection attempts indicative of scanning activity, one device was detected transferring suspicious files over SMB to other internal devices. The device was then observed connecting to another internal device via SMB and continuing suspicious file activity, such as appending files on network shares with the “.akira” extension, and performing suspicious writes to SMB shares on other internal devices.

Darktrace’s autonomous threat investigator, Cyber AI Analyst™, was able to analyze the multiple events related to this encryption activity and collate them into one AI Analyst incident, presenting a detailed and comprehensive summary of the entire incident within 10 minutes of Darktrace’s initial detection. Rather than simply viewing individual breaches as standalone activity, AI Analyst can identify the individual steps of an ongoing attack to provide complete visibility over emerging compromises and their kill chains. Not only does this bolster the network’s defenses, but the autonomous investigations carried out by AI Analyst also help to save the security team’s time and resources in triaging and monitoring ongoing incidents.

Figure 3: Darktrace Cyber AI Analyst incident correlated multiple model breaches together to show Akira ransomware encryption activity.

In addition to analyzing and compiling Darktrace model breaches, AI Analyst also leveraged the host-level insights provided by Microsoft Defender to enrich its investigation into the encryption event. By using the Security Integration model breaches, AI Analyst can retrieve timestamp and device details from a Defender alert and further investigate any unusual activity surrounding the alert to present a full picture of the suspicious activity.

In customer B’s environment, following the unusual RDP sessions and rare external connections using the AnyDesk user agent, an affected device was later observed writing around 2,000 files named "akira_readme.txt" to multiple internal SMB shares. This represented the malicious actor dropping ransom notes, containing the demands and extortion attempts of the actors.

Figure 4: Model Breach Event Log indicating the ransom note detected on May 12, 2023, which led to the Darktrace DETECT model breach, Anomalous Server Activity / Write to Network Accessible WebRoot.
Figure 5: Packet Capture (PCAP) demonstrating the Akira ransom note captured from the connection details seen in Figure 4.

As a result of this ongoing activity, an Enhanced Monitoring model breach, a high-fidelity detection model type that detects activities that are more likely to be indicative of compromise, was escalated to Darktrace’s Security Operations Center (SOC) who, in turn were able to further investigate and triage this ransomware activity. Customers who have subscribed to Darktrace’s Proactive Threat Notification (PTN) service would receive an alert from the SOC team, advising urgent follow up action.

Darktrace detection models observed during ransomware deployment:

  • Security Integration / Integration Ransomware Incident
  • Security Integration / High Severity Integration Detection
  • Security Integration / Integration Ransomware Detected
  • Device / Suspicious File Writes to Multiple Hidden SMB Shares
  • Compliance / SMB Drive Write
  • Compromise / Ransomware / Suspicious SMB Activity (Proactive Threat Notification Alerted by the Darktrace SOC)
  • Anomalous File / Internal / Additional Extension Appended to SMB File
  • Anomalous File / Internal / Unusual SMB Script Write
  • Compromise / Ransomware / Ransom or Offensive Words Written to SMB
  • Anomalous Server Activity /Write to Network Accessible WebRoot
  • Anomalous Server Activity /Write to Network Accessible WebRoot

Darktrace autonomous response neutralizes Akira Ransomware

When Darktrace is configured in autonomous response mode, it is able to follow up successful threat identifications with instant autonomous actions that stop malicious actors in their tracks and prevent them from achieving their end goals.

In the examples of Darktrace customers affected by Akira Ransomware outlined above, only customer A had autonomous response mode enabled during their ransomware attack. The autonomous response capability of Darktrace helped the customer to minimize disruption to the business through multiple targeted actions on devices affected by ransomware.

One action carried out by Darktrace's Autonomous Respose was to block all on-going traffic from affected devices. In doing so, Darktrace effectively shuts down communications between devices affected by Akira and the malicious infrastructure used by threat actors, preventing the spread of data on the client network or threat actor payloads.

Another crucial response action applied on this customer’s network was combat Akira was to “Enforce a Pattern of Life” on affected devices. This action is designed to prevent devices from performing any activity that would constitute a deviation from their expected behavior, while allowing them to continue their ‘usual’ business operations without causing any disruption.

While the initial intrusion of the attack on customer A’s network likely fell outside of the scope of Darktrace’s visibility, Darktrace was able to minimize the disruption caused by Akira, containing the ransomware and allowing the customer to further investigate and remediate.

Darktrace Autonomous Response model breaches:

  • Antigena / Network / External Threat / Antigena Ransomware Block
  • Antigena / Network / External Threat / Antigena Suspicious Activity Block
  • Antigena / Network / Significant Anomaly / Antigena Enhanced Monitoring from Server Block
  • Antigena / Network / External Threat / Antigena Suspicious Activity Block
  • Antigena / Network / External Threat / Antigena File then New Outbound Block
  • Antigena / Network / Insider Threat / Antigena Unusual Privileged User Activities Block
  • Antigena / Network / Significant Anomaly / Antigena Breaches Over Time Block
  • Antigena / Network / Significant Anomaly / Antigena Significant Anomaly from Client Block
  • Antigena / Network /Insider Threat /Antigena SMB Enumeration Block

Conclusion

The impact of cyber attacks

Novel ransomware strains like Akira Ransomware present a significant challenge to security teams across the globe due to the constant evolution of attack methods and tactics, making it huge a challenge for security teams to stay up to date with the most current threat intelligence.  

Therefore, it is paramount for organizations to adopt a technology designed around an intelligent decision maker able to identify unusual activity that could be indicative of a ransomware attack without depending solely on rules, signatures, or statistic lists of malicious IoCs.

Importance of AI-powered cybersecurity solutions

Darktrace identified Akira ransomware at every stage of the attack’s kill chain on multiple customer networks, even when threat actors were utilizing seemingly legitimate services (or spoofed versions of them) to carry out malicious activity. While this may have gone unnoticed by traditional security tools, Darktrace’s anomaly-based detection enabled it to recognize malicious activity for what it was. When enabled in autonomous response mode, Darktrace is able to follow up initial detections with machine-speed preventative actions to stop the spread of ransomware and minimize the damage caused to customer networks.  

There is no silver bullet to defend against novel cyber-attacks, however Darktrace’s anomaly-based approach to threat detection and autonomous response capabilities are uniquely placed to detect and respond to cyber disruption without latency.

Credit to: Manoel Kadja, Cyber Analyst, Nahisha Nobregas, SOC Analyst.

Appendices

IOC - Type - Description/Confidence

202.175.136[.]197 - External destination IP -Incoming RDP Connection

api.playanext[.]com - External hostname - Possible RDP Host

.akira - File Extension - Akira Ransomware Extension

akira_readme.txt - Text File - Akira Ransom Note

AnyDesk/7.1.11 - User Agent -AnyDesk User Agent

MITRE ATT&CK Mapping

Tactic & Technique

DISCOVERY

T1083 - File and Directory Discovery

T1046 - Network Service Scanning

T1135 - Network Share Discovery

RECONNAISSANCE

T1595.002 - Vulnerability Scanning

CREDENTIAL ACCESS, COLLECTION

T1557.001 - LLMNR/NBT-NS Poisoning and SMB Relay

DEFENSE EVASION, LATERAL MOVEMENT

T1550.002 - Pass the Hash

DEFENSE EVASION, PERSISTENCE, PRIVILEGE ESCALATION, INITIAL ACCESS

T1078 - Valid Accounts

DEFENSE EVASION

T1006 - Direct Volume Access

LATERAL MOVEMENT

T1563.002 - RDP Hijacking

T1021.001 - Remote Desktop Protocol

T1080 - Taint Shared Content

T1021.002 - SMB/Windows Admin Shares

INITIAL ACCESS

T1190 - Exploit Public-Facing Application

T1199 - Trusted Relationship

PERSISTENCE, INITIAL ACCESS

T1133 - External Remote Services

PERSISTENCE

T1505.003 - Web Shell

IMPACT

T1486 - Data Encrypted for Impact

References

[1] https://www.bleepingcomputer.com/news/security/meet-akira-a-new-ransomware-operation-targeting-the-enterprise/

[2] https://www.civilsdaily.com/news/cert-in-warns-against-akira-ransomware/#:~:text=Spread%20Methods%3A%20Akira%20ransomware%20is,Desktop%20connections%20to%20infiltrate%20systems

[3] https://hybrid-analysis.com/sample/0ee9baef94c80647eed30fa463447f000ec1f50a49eecfb71df277a2ca1fe4db?environmentId=100

Get the latest insights on emerging cyber threats

This report explores the latest trends shaping the cybersecurity landscape and what defenders need to know in 2026.

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
Manoel Kadja
Cyber Analyst

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June 2, 2026

Stopping Stealth Attacks with Precision: How Núclea Prevented a Breach Without Disruption

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Núclea is a Brazilian data and technology company that supports the country’s financial system by delivering digital services exclusively to banks and financial institutions. Operating in an environment where trust, availability, and data integrity are critical, the company faces a threat landscape that has evolved rapidly—particularly with the rise of AI-driven cyberattacks.

Brazil has experienced a wave of successful cyber incidents targeting financial institutions, many of them enabled by insiders or compromised credentials. The result was a noticeable shift in attacker strategy: instead of focusing on end customers, threat actors began targeting the institutions and platforms that underpin the financial ecosystem itself.

“Attacks became far more directed and contextual,” explains Guilherme, who leads incident response within Núclea’s security platform engineering team. “They weren’t noisy or obviously malicious—they were precise, patient, and designed to blend into normal operations.”

That precision was on full display in January 2026, when Núclea faced one of the most convincing phishing attacks the team had seen.

A real attack, built on trust and context

The attack began with a seemingly routine email.

It was sent from a real Brazilian government institution, using legitimate infrastructure and valid credentials that were later confirmed to have been compromised. Núclea had an established, ongoing relationship with this organization, and the email’s language, tone, and subject matter aligned perfectly with the type of communication the recipient team handled every day.

Attached to the email was a PDF document containing content that looked entirely legitimate.

The problem? A single URL embedded inside that PDF.

“The message itself was correct. The sender was real. The context was familiar. Even the document content made sense,” Guilherme explains. “There was just one small element that didn’t belong.”

That small detail was enough to initiate a full attack chain.

What the attackers were trying to do

If clicked, the URL would have downloaded a malicious payload designed to:

  • Collect information about the user and device
  • Identify where the system was located within the financial ecosystem
  • Install remote access tools to maintain control
  • Deploy an infostealer to extract sensitive data
  • Execute anti-forensic scripts to erase traces of the intrusion

In other words, it was a carefully engineered operation designed for persistence and stealth, not immediate disruption.

The attack also employed urgency—a classic social engineering technique. When the link didn’t open as expected, employees requested assistance from the security team, insisting the document was important and needed to be accessed quickly.

This is precisely the kind of scenario where traditional security tools struggle: almost everything about the interaction is legitimate.

Where Darktrace made the difference

Instead of blocking the entire message or relying on known indicators of compromise, Darktrace focused on behavioral context.

Darktrace recognized:

  • That the sending organization was normally trusted
  • That the communication pattern matched historical behavior
  • That the PDF content itself was not suspicious

But it also identified that the URL embedded within the document deviated from established behavioral patterns.

Rather than disrupting business operations, Darktrace took precise action: it rewrote the URL, preventing the malicious download while leaving the rest of the email untouched.

“When we analyzed it afterward, it became clear how dangerous the attack would have been,” says Guilherme. “But it never progressed—because Darktrace acted at exactly the right point.”

Subsequent forensic analysis confirmed the payload’s malicious intent. The attack never succeeded.

Precision over disruption

For Núclea, this incident reinforced a critical lesson: modern attacks don’t always look malicious—they hide within normal activity.

“What stands out to me is the precision,” Guilherme says. “Darktrace doesn’t rely on big, obvious signals. It’s effective in situations that fall outside the standard patterns we all know.”

Building resilience in a high trust ecosystem

For Núclea, cybersecurity is not just a defensive measure—it’s a business enabler.

Availability failures or successful breaches in the financial ecosystem can have immediate, large-scale consequences, from financial loss to reputational damage. Preventing those outcomes protects not just Núclea, but its partners and customers as well.

“Cyber resilience means keeping the business running—even under attack,” Guilherme explains. “And that requires people, processes, and technology working together.”

As AI continues to accelerate both attacks and defenses, the role of security is evolving. Precision, behavioral understanding, and intelligent automation are no longer optional—they’re essential.

“The easy days were yesterday,” Guilherme says. “The challenges ahead are bigger. We need to be prepared—internally and with partners that help us build resilience.”

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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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About the author
Dr. Oakley Cox-Robinson
Senior Director of Product
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