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January 8, 2024

Uncovering CyberCartel Threats in Latin America

Examine the growing threat of cyber cartels in Latin America and learn how to safeguard against their attacks.
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
Alexandra Sentenac
Cyber Analyst
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08
Jan 2024

Introduction

In September 2023, Darktrace published its first Half-Year Threat Report, highlighting Threat Research, Security Operation Center (SOC), model breach, and Cyber AI Analyst analysis and trends across the Darktrace customer fleet. According to Darktrace’s Threat Report, the most observed threat type to affect Darktrace customers during the first half of 2023 was Malware-as-a-Service (Maas). The report highlighted a growing trend where malware strains, specifically in the MaaS ecosystem, “use cross-functional components from other strains as part of their evolution and customization” [1].  

Darktrace’s Threat Research team assessed this ‘Frankenstein’ approach would very likely increase, as shown by the fact that indicators of compromise (IoCs) are becoming “less and less mutually exclusive between malware strains as compromised infrastructure is used by multiple threat actors through access brokers or the “as-a-Service” market” [1].

Darktrace investigated one such threat during the last months of summer 2023, eventually leading to the discovery of CyberCartel-related activity across a significant number of Darktrace customers, especially in Latin America.

CyberCartel Overview and Darktrace Coverage

During a threat hunt, Darktrace’s Threat Research team discovered the download of a binary with a unique Uniform Resource Identifier (URI) pattern. When examining Darktrace’s customer base, it was discovered that binaries with this same URI pattern had been downloaded by a significant number of customer accounts, especially by customers based in Latin America. Although not identical, the targets and tactics, techniques, and procedures (TTPs) resembled those mentioned in an article regarding a botnet called Fenix [2], particularly active in Latin America.

During the Threat Research team’s investigation, nearly 40 potentially affected customer accounts were identified. Darktrace’s global Threat Research team investigates pervasive threats across Darktrace’s customer base daily. This cross-fleet research is based on Darktrace’s anomaly-based detection capability, Darktrace DETECT™, and revolves around technical analysis and contextualization of detection information.

Amid the investigation, further open-source intelligence (OSINT) research revealed that most indicators observed during Darktrace’s investigations were associated to a Latin American threat group named CyberCartel, with a small number of IoCs being associated with the Fenix botnet. While CyberCartel seems to have been active since 2012 and relies on MaaS offerings from well-known malware families, Fenix botnet was allegedly created at the end of last year and “specifically targets users accessing government services, particularly tax-paying individuals in Mexico and Chile” [2].

Both groups share similar targets and TTPs, as well as objectives: installing malware with information-stealing capabilities. In the case of Fenix infections, the compromised device will be added to a botnet and execute tasks given by the attacker(s); while in the case of CyberCartel, it can lead to various types of second-stage info-stealing and Man-in-the-Browser capabilities, including retrieving system information from the compromised device, capturing screenshots of the active browsing tab, and redirecting the user to fraudulent websites such as fake banking sites. According to a report by Metabase Q [2], both groups possibly share command and control (C2) infrastructure, making accurate attribution and assessment of the confidence level for which group was affecting the customer base extremely difficult. Indeed, one of the C2 IPs (104.156.149[.]33) observed on nearly 20 customer accounts during the investigation had OSINT evidence linking it to both CyberCartel and Fenix, as well as another group known to target Mexico called Manipulated Caiman [3] [4] [5].

CyberCartel and Fenix both appear to target banking and governmental services’ users based in Latin America, especially individuals from Mexico and Chile. Target institutions purportedly include tax administration services and several banks operating in the region. Malvertising and phishing campaigns direct users to pages imitating the target institutions’ webpages and prompt the download of a compressed file advertised in a pop-up window. This file claims enhance the user’s security and privacy while navigating the webpage but instead redirects the user to a compromised website hosting a zip file, which itself contains a URL file containing instructions for retrieval of the first stage payload from a remote server.

pop-up window with malicious file
Figure 1: Example of a pop-up window asking the user to download a compressed file allegedly needed to continue navigating the portal. Connections to the domain srlxlpdfmxntetflx[.]com were observed in one account investigated by Darktrace

During their investigations, the Threat Research team observed connections to 100% rare domains (e.g., situacionfiscal[.]online, consultar-rfc[.]online, facturmx[.]info), many of them containing strings such as “mx”, “rcf” and “factur” in their domain names, prior to the downloads of files with the unique URI pattern identified during the aforementioned threat hunting session.

The reference to “rfc” is likely a reference to the Registro Federal de Contribuyentes, a unique registration number issued by Mexico’s tax collection agency, Servicio de Administración Tributaria (SAT). These domains were observed as being 100% rare for the environment and were connected to a few minutes prior to connections to CyberCartel endpoints. Most of the endpoints were newly registered, with creation dates starting from only a few months earlier in the first half of 2023. Interestingly, some of these domains were very similar to legitimate government websites, likely a tactic employed by threat actors to convince users to trust the domains and to bypass security measures.

Figure 2: Screenshot from similarweb[.]com showing the degree of affinity between malicious domains situacionfiscal[.]online and facturmx[.]info and the legitimate Mexican government hostname sat[.]gob[.]mx
Figure 3: Screenshot of the likely source infection website facturmx[.]info taken when visited in a sandbox environment

In other customer networks, connections to mail clients were observed, as well as connections to win-rar[.]com, suggesting an interaction with a compressed file. Connections to legitimate government websites were also detected around the same time in some accounts. Shortly after, the infected devices were detected connecting to 100% rare IP addresses over the HTTP protocol using WebDAV user agents such as Microsoft-WebDAV-MiniRedir/10.0.X and DavCInt. Web Distributed Authoring and Versioning, in its full form, is a legitimate extension to the HTTP protocol that allows users to remotely share, copy, move and edit files hosted on a web server. Both CyberCartel and Fenix botnet reportedly abuse this protocol to retrieve the initial payload via a shortcut link. The use (or abuse) of this protocol allows attackers to evade blocklists and streamline payload distribution. In cases investigated by Darktrace, the use of this protocol was not always considered unusual for the breach device, indicating it also was commonly used for its legitimate purposes.

HTTP methods observed included PROPFIND, GET, and OPTIONS, where a higher proportion of PROPFIND requests were observed. PROPFIND is an HTTP method related to the use of WebDAV that retrieves properties in an exactly defined, machine-readable, XML document (GET responses do not have a define format). Properties are pieces of data that describe the state of a resource, i.e., data about data [7]. They are used in distributed authoring environments to provide for efficient discovery and management of resources.  

Figure 4: Device event log showing a connection to facturmx[.]info followed by a WebDAV connection to the 100% rare IP 172.86.68[.]104

In a number of cases, connections to compromised endpoints were followed by the download of one or more executable files with names following the regex pattern /(yes|4496|[A-Za-z]{8})/(((4496|4545)[A-Za-z]{24})|Herramienta_de_Seguridad_SII).(exe|jse), for example 4496UCJlcqwxvkpXKguWNqNWDivM.exe. PROPFIND and GET HTTP requests for dynamic-link library (DLL) files such as urlmon.dll and netutils.dll were also detected. These are legitimate Windows files that are essential to handle network and internet-related tasks in Windows. Irrespective of whether they had malicious or legitimate signatures, Darktrace DETECT was able to recognize that the download of these files was suspicious with rare external endpoints not previously observed on the respective customer networks.

Figure 5: Advanced Search results showing some of the HTTP requests made by the breach device to a CyberCartel endpoint via PROPFIND, GET, or OPTIONS methods for executable and DLL files

Following Darktrace DETECT’s model breaches, these HTTP connections were investigated by Cyber AI Analyst™. AI Analyst provided a summary and further technical details of these connections, as shown in figure 6.

Figure 6: Cyber AI Analyst incident showing a summary of the event, as well as technical details. The AI investigation process is also detailed

AI Analyst searched for all HTTP connections made by the breach device and found more than 2,500 requests to more than a hundred endpoints for one given device. It then looked for the user agents responsible for these connections and found 15 possible software agents responsible for the HTTP requests, and from these identified a single suspicious software agent, Microsoft-WebDAV-Min-Redir. As mentioned previously, this is a legitimate software, but its use by the breach device was considered unusual by Darktrace’s machine learning technology. By performing analysis on thousands of connections to hundreds of endpoints at machine speed, AI Analyst is able to perform the heavy lifting on behalf of human security teams and then collate its findings in a single summary pane, giving end-users the information needed to assess a given activity and quickly start remediation as needed. This allows security teams and administrators to save precious time and provides unparalleled visibility over any potentially malicious activity on their network.

Following the successful identification of CyberCartel activity by DETECT, Darktrace RESPOND™ is then able to contain suspicious behavior, such as by restricting outgoing traffic or enforcing normal patterns of life on affected devices. This would allow customer security teams extra time to analyze potentially malicious behavior, while leaving the rest of the network free to perform business critical operations. Unfortunately, in the cases of CyberCartel compromises detected by Darktrace, RESPOND was not enabled in autonomous response mode meaning preventative actions had to be applied manually by the customer’s security team after the fact.

Figure 7. Device event log showing connections to 100% rare CyberCartel endpoint 172.86.68[.]194 and subsequent suggested RESPOND actions.

Conclusion

Threat actors targeting high-value entities such as government offices and banks is unfortunately all too commonplace.  In the case of Cyber Cartel, governmental organizations and entities, as well as multiple newspapers in the Latin America, have cautioned users against these malicious campaigns, which have occurred over the past few years [8] [9]. However, attackers continuously update their toolsets and infrastructure, quickly rendering these warnings and known-bad security precautions obsolete. In the case of CyberCartel, the abuse of the legitimate WebDAV protocol to retrieve the initial payload is just one example of this. This method of distribution has also been leveraged by in Bumblebee malware loader’s latest campaign [10]. The abuse of the legitimate WebDAV protocol to retrieve the initial CyberCartel payload outlined in this case is one example among many of threat actors adopting new distribution methods used by others to further their ends.

As threat actors continue to search for new ways of remaining undetected, notably by incorporating legitimate processes into their attack flow and utilizing non-exclusive compromised infrastructure, it is more important than ever to have an understanding of normal network operation in order to detect anomalies that are indicative of an ongoing compromise. Darktrace’s suite of products, including DETECT+RESPOND, is well placed to do just that, with machine-speed analysis, detection, and response helping security teams and administrators keep their digital environments safe from malicious actors.

Credit to: Nahisha Nobregas, SOC Analyst

References

[1] https://darktrace.com/blog/darktrace-half-year-threat-report

[2] https://www.metabaseq.com/fenix-botnet/

[3] https://perception-point.io/blog/manipulated-caiman-the-sophisticated-snare-of-mexicos-banking-predators-technical-edition/

[4] https://www.virustotal.com/gui/ip-address/104.156.149.33/community

[5] https://silent4business.com/tendencias/1

[6] https://www.metabaseq.com/cybercartel/

[7] http://www.webdav.org/specs/rfc2518.html#rfc.section.4.1

[8] https://www.csirt.gob.cl/alertas/8ffr23-01415-01/

[9] https://www.gob.mx/sat/acciones-y-programas/sitios-web-falsos

[10] https://www.bleepingcomputer.com/news/security/bumblebee-malware-returns-in-new-attacks-abusing-webdav-folders/

Appendices  

Darktrace DETECT Model Detections

AI Analyst Incidents:

• Possible HTTP Command and Control

• Suspicious File Download

Model Detections:

• Anomalous Connection / New User Agent to IP Without Hostname

• Device / New User Agent and New IP

• Anomalous File / EXE from Rare External Location

• Multiple EXE from Rare External Locations

• Anomalous File / Script from Rare External Location

List of IoCs

IoC - Type - Description + Confidence

f84bb51de50f19ec803b484311053294fbb3b523 - SHA1 hash - Likely CyberCartel Payload IoCs

4eb564b84aac7a5a898af59ee27b1cb00c99a53d - SHA1 hash - Likely CyberCartel payload

8806639a781d0f63549711d3af0f937ffc87585c - SHA1 hash - Likely CyberCartel payload

9d58441d9d31b5c4011b99482afa210b030ecac4 - SHA1 hash - Possible CyberCartel payload

37da048533548c0ad87881e120b8cf2a77528413 - SHA1 hash - Likely CyberCartel payload

2415fcefaf86a83f1174fa50444be7ea830bb4d1 - SHA1 hash - Likely CyberCartel payload

15a94c7e9b356d0ff3bcee0f0ad885b6cf9c1bb7 - SHA1 hash - Likely CyberCartel payload

cdc5da48fca92329927d9dccf3ed513dd28956af - SHA1 hash - Possible CyberCartel payload

693b869bc9ba78d4f8d415eb7016c566ead839f3 - SHA1 hash - Likely CyberCartel payload

04ce764723eaa75e4ee36b3d5cba77a105383dc5 - SHA1 hash - Possible CyberCartel payload

435834167fd5092905ee084038eee54797f4d23e - SHA1 hash - Possible CyberCartel payload

3341b4f46c2f45b87f95168893a7485e35f825fe - SHA1 hash - Likely CyberCartel payload

f6375a1f954f317e16f24c94507d4b04200c63b9 - SHA1 hash - Likely CyberCartel payload

252efff7f54bd19a5c96bbce0bfaeeecadb3752f - SHA1 hash - Likely CyberCartel payload

8080c94e5add2f6ed20e9866a00f67996f0a61ae - SHA1 hash - Likely CyberCartel payload

c5117cedc275c9d403a533617117be7200a2ed77 - SHA1 hash - Possible CyberCartel payload

19dd866abdaf8bc3c518d1c1166fbf279787fc03 - SHA1 hash - Likely CyberCartel payload

548287c0350d6e3d0e5144e20d0f0ce28661f514 - SHA1 hash - Likely CyberCartel payload

f0478e88c8eefc3fd0a8e01eaeb2704a580f88e6 - SHA1 hash - Possible CyberCartel payload

a9809acef61ca173331e41b28d6abddb64c5f192 - SHA1 hash - Likely CyberCartel payload

be96ec94f8f143127962d7bf4131c228474cd6ac - SHA1 hash -Likely CyberCartel payload

44ef336395c41bf0cecae8b43be59170bed6759d - SHA1 hash - Possible CyberCartel payload

facturmx[.]info - Hostname - Likely CyberCartel infection source

consultar-rfc[.]online - Hostname - Possible CyberCartel infection source

srlxlpdfmxntetflx[.]com - Hostname - Likely CyberCartel infection source

facturmx[.]online - Hostname - Possible CyberCartel infection source

rfcconhomoclave[.]mx - Hostname - Possible CyberCartel infection source

situacionfiscal[.]online - Hostname - Likely CyberCartel infection source

descargafactura[.]club - Hostname - Likely CyberCartel infection source

104.156.149[.]33 - IP - Likely CyberCartel C2 endpoint

172.86.68[.]194 - IP - Likely CyberCartel C2 endpoint

139.162.73[.]58 - IP - Likely CyberCartel C2 endpoint

172.105.24[.]190 - IP - Possible CyberCartel C2 endpoint

MITRE ATT&CK Mapping

Tactic - Technique

Command and Control - Ingress Tool Transfer (T1105)

Command and Control - Web Protocols (T1071.001)

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
Alexandra Sentenac
Cyber Analyst

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June 3, 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 2, 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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