December 15, 2023

How Darktrace Halted A DarkGate in MS Teams

Discover how Darktrace thwarted DarkGate malware in Microsoft Teams. Stay informed on the latest cybersecurity measures and protect your business.

Written by

Natalia Sánchez Rocafort

Cyber Security Analyst

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

Natalia Sánchez Rocafort

Cyber Security Analyst

Dec 2023

Securing Microsoft Teams and SharePoint

Given the prevalence of the Microsoft Teams and Microsoft SharePoint platforms in the workplace in recent years, it is essential that organizations stay vigilant to the threat posed by applications vital to hybrid and remote work and prioritize the security and cyber hygiene of these services. For just as the use of these platforms has increased exponentially with the rise of remote and hybrid working, so too has the malicious use of them to deliver malware to unassuming users.

Researchers across the threat landscape have begun to observe these legitimate services being leveraged by malicious actors as an initial access method. Microsoft Teams can easily be exploited to send targeted phishing messages to individuals within an organization, while appearing legitimate and safe. Although the exact contents of these messages may vary, the messages frequently use social engineering techniques to lure users to click on a SharePoint link embedded into the message. Interacting with the malicious link will then download a payload [1].

Darktrace observed one such malicious attempt to use Microsoft Teams and SharePoint in September 2023, when a device was observed downloading DarkGate, a commercial trojan that is known to deploy other strains of malware, also referred to as a commodity loader [2], after clicking on SharePoint link. Fortunately for the customer, Darktrace’s suite of products was perfectly poised to identify the initial signs of suspicious activity and Darktrace RESPOND™ was able to immediately halt the advancement of the attack.

DarkGate Attack Overview

On September 8, 2023, Darktrace DETECT™ observed around 30 internal devices on a customer network making unusual SSL connections to an external SharePoint site which contained the name of a person, 'XXXXXXXX-my.sharepoint[.]com' (107.136[.]8, 13.107.138[.]8). The organization did not have any employees who went by this name and prior to this activity, no internal devices had been seen contacting the endpoint.

At first glance, this initial attack vector would have appeared subtle and seemingly trustworthy to users. Malicious actors likely sent various users a phishing message via Microsoft Teams that contained the spoofed SharePoint link to the personalized SharePoint link ''XXXXXXXX-my.sharepoint[.]com'.

Figure 1: Advanced Search query showing a sudden spike in connections to ''XXXXXXXX -my.sharepoint[.]com'.

Darktrace observed around 10 devices downloading approximately 1 MB of data during their connections to the Sharepoint endpoint. Darktrace DETECT observed some of the devices making subsequent HTTP GET requests to a range of anomalous URIs. The devices utilized multiple user-agents for these connections, including ‘curl’, a command line tool that allows individuals to request and transfer data from a specific URL. The connections were made to the IP 5.188.87[.]58, an endpoint that has been flagged as an indicator of compromise (IoC) for DarkGate malware by multiple open-source intelligence (OSINT) sources [3], commonly associated with HTTP GET requests:

GET request over port 2351 with the User-Agent header 'Mozilla/4.0 (compatible; Win32; WinHttp.WinHttpRequest.5)' and the target URI '/bfyxraav' to 5.188.87[.]58
GET request over port 2351 with the user-agent header 'curl' and the target URI '/' to 5.188.87[.]58
GET request over port 2351 with the user-agent header 'curl/8.0.1' and the target URI '/msibfyxraav' to 5.188.87[.]58

The HTTP GET requests made with the user-agent header 'curl' and the target URI '/' to 5.188.87[.]58 were responded to with a filename called 'Autoit3.exe'. The other requests received script files with names ending in '.au3, such as 'xkwtvq.au3', 'otxynh.au3', and 'dcthbq.au3'. DarkGate malware has been known to make use of legitimate AutoIt files, and typically runs multiple AutoIt scripts (‘.au3’) [4].

Following these unusual file downloads, the devices proceeded to make hundreds of HTTP POST requests to the target URI '/' using the user-agent header 'Mozilla/4.0 (compatible; Synapse)' to 5.188.87[.]58. The contents of these requests, along with the contents of the responses, appear to be heavily obfuscated.

Figure 2: Example of obfuscated response, as shown in a packet capture downloaded from Darktrace.

While Microsoft’s Safe Attachments and Safe Links settings were unable to detect this camouflaged malicious activity, Darktrace DETECT observed the unusual over-the-network connectivity that occurred. While Darktrace DETECT identified multiple internal devices engaging in this anomalous behavior throughout the course of the compromise, the activity observed on one device in particular best showcases the overall kill chain of this attack.

The device in question was observed using two different user agents (curl/8.0.1 and Mozilla/4.0 (compatible; Win32; WinHttp.WinHttpRequest.5)) when connecting to the endpoint 5.188.87[.]58 and target URI ‘/bfyxraav’. Additionally, Darktrace DETECT recognized that it was unusual for this device to be making these HTTP connections via destination port 2351.

As a result, Darktrace’s Cyber AI Analyst™ launched an autonomous investigation into the suspicious activity and was able to connect the unusual external connections together, viewing them as one beaconing incident as opposed to isolated series of connections.

Figure 3: Cyber AI Analyst investigation summarizing the unusual repeated connections made to 5.188.87[.]58 via destination port 2351.

Darktrace then observed the device downloading the ‘Autoit3.exe’ file. Darktrace RESPOND took swift mitigative action by blocking similar connections to this endpoint, preventing the device from downloading any additional suspicious files.

Figure 4: Suspicious ‘Autoit3.exe’ downloaded by the source device from the malicious external endpoint.

Just one millisecond later, Darktrace observed the device making suspicious HTTP GET requests to URIs including ‘/msibfyxraav’. Darktrace recognized that the device had carried out several suspicious actions within a relatively short period of time, breaching multiple DETECT models, indicating that it may have been compromised. As a result, RESPOND took action against the offending device by preventing it from communicating externally [blocking all outbound connections] for a period of one hour, allowing the customer’s security team precious time to address the issue.

It should be noted that, at this point, had the customer subscribed to Darktrace’s Proactive Threat Notification (PTN) service, the Darktrace Security Operations Center (SOC) would have investigated these incidents in greater detail, and likely would have sent a notification directly to the customer to inform them of the suspicious activity.

Additionally, AI Analyst collated various distinct events and suggested that these stages were linked as part of an attack. This type of augmented understanding of events calculated at machine speed is extremely valuable since it likely would have taken a human analyst hours to link all the facets of the incident together.

Figure 5: AI Analyst investigation showcasing the use of the ‘curl’ user agent to connect to the target URI ‘/msibfyxraav’.

Figure 6: Darktrace RESPOND moved to mitigate any following connections by blocking all outgoing traffic for 1 hour.

Following this, an automated investigation was launched by Microsoft Defender for Endpoint. Darktrace is designed to coordinate with multiple third-party security tools, allowing for information on ongoing incidents to be seamlessly exchanged between Darktrace and other security tools. In this instance, Microsoft Defender identified a ‘low severity’ incident on the device, this automatically triggered a corresponding alert within DETECT, presented on the Darktrace Threat Visuallizer.

The described activity occurred within milliseconds. At each step of the attack, Darktrace RESPOND took action either by enforcing expected patterns of life [normality] on the affected device, blocking connections to suspicious endpoints for a specified amount of time, and/or blocking all outgoing traffic from the device. All the relevant activity was detected and promptly stopped for this device, and other compromised devices, thus containing the compromise and providing the security team invaluable remediation time.

Figure 7: Overview of the compromise activity, all of which took place within a matter of miliseconds.

Darktrace identified similar activity on other devices in this customer’s network, as well as across Darktrace’s fleet around the same time in early September.

On a different customer environment, Darktrace DETECT observed more than 25 ‘.au3’ files being downloaded; this activity can be seen in Figure 9.

Figure 8: High volume of file downloads following GET request and 'curl' commands.

Figure 9 provides more details of this activity, including the source and destination IP addresses (5.188.87[.]58), the destination port, the HTTP method used and the MIME/content-type of the file

Figure 9: Additional information of the anomalous connections.

A compromised server in another customer deployment was seen establishing unusual connections to the external IP address 80.66.88[.]145 – an endpoint that has been associated with DarkGate by OSINT sources [5]. This activity was identified by Darktrace/DETECT as a new connection for the device via an unusual destination port, 2840. As the device in question was a critical server, Darktrace DETECT treated it with suspicion and generated an ‘Anomalous External Activity from Critical Network Device’ model breach.

Figure 10: Model breach and model breach event log for suspicious connections to additional endpoint.

Conclusion

While Microsoft Teams and SharePoint are extremely prominent tools that are essential to the business operations of many organizations, they can also be used to compromise via living off the land, even at initial intrusion. Any Microsoft Teams user within a corporate setting could be targeted by a malicious actor, as such SharePoint links from unknown senders should always be treated with caution and should not automatically be considered as secure or legitimate, even when operating within legitimate Microsoft infrastructure.

Malicious actors can leverage these commonly used platforms as a means to carry out their cyber-attacks, therefore organizations must take appropriate measures to protect and secure their digital environments. As demonstrated here, threat actors can attempt to deploy malware, like DarkGate, by targeting users with spoofed Microsoft Teams messages. By masking malicious links as legitimate SharePoint links, these attempts can easily convince targets and bypass traditional security tools and even Microsoft’s own Safe Links and Safe Attachments security capabilities.

When the chain of events of an attack escalates within milliseconds, organizations must rely on AI-driven tools that can quickly identify and automatically respond to suspicious events without latency. As such, the value of Darktrace DETECT and Darktrace RESPOND cannot be overstated. Given the efficacy and efficiency of Darktrace’s detection and autonomous response capabilities, a more severe network compromise in the form of the DarkGate commodity loader was ultimately averted.

Credit to Natalia Sánchez Rocafort, Cyber Security Analyst, Zoe Tilsiter.

Appendices

Darktrace DETECT Model Detections

[Model Breach: Device / Initial Breach Chain Compromise 100% –– Breach URI: /#modelbreach/114039 ] (Enhanced Monitoring)· [Model Breach: Device / Initial Breach Chain Compromise 100% –– Breach URI: /#modelbreach/114124 ] (Enhanced Monitoring)
[Model Breach: Device / New User Agent and New IP 62% –– Breach URI: /#modelbreach/114030 ]
[Model Breach: Anomalous Connection / Application Protocol on Uncommon Port 46% –– Breach URI: /#modelbreach/114031 ]
[Model Breach: Anomalous Connection / New User Agent to IP Without Hostname 62% –– Breach URI: /#modelbreach/114032 ]
[Model Breach: Device / New User Agent 32% –– Breach URI: /#modelbreach/114035 ]
[Model Breach: Device / Three Or More New User Agents 31% –– Breach URI: /#modelbreach/114036 ]
[Model Breach: Anomalous Server Activity / Anomalous External Activity from Critical Network Device 62% –– Breach URI: /#modelbreach/612173 ]
[Model Breach: Anomalous File / EXE from Rare External Location 61% –– Breach URI: /#modelbreach/114037 ]
[Model Breach: Anomalous Connection / Multiple Connections to New External TCP Port 61% –– Breach URI: /#modelbreach/114042 ]
[Model Breach: Security Integration / Integration Ransomware Detected 100% –– Breach URI: /#modelbreach/114049 ]
[Model Breach: Compromise / Beaconing Activity To External Rare 62% –– Breach URI: /#modelbreach/114059 ]
[Model Breach: Compromise / HTTP Beaconing to New Endpoint 30% –– Breach URI: /#modelbreach/114067 ]
[Model Breach: Security Integration / C2 Activity and Integration Detection 100% –– Breach URI: /#modelbreach/114069 ]
[Model Breach: Anomalous File / EXE from Rare External Location 55% –– Breach URI: /#modelbreach/114077 ]
[Model Breach: Compromise / High Volume of Connections with Beacon Score 66% –– Breach URI: /#modelbreach/114260 ]
[Model Breach: Security Integration / Low Severity Integration Detection 59% –– Breach URI: /#modelbreach/114293 ]
[Model Breach: Security Integration / Low Severity Integration Detection 33% –– Breach URI: /#modelbreach/114462 ]
[Model Breach: Security Integration / Integration Ransomware Detected 100% –– Breach URI: /#modelbreach/114109 ]· [Model Breach: Device / Three Or More New User Agents 31% –– Breach URI: /#modelbreach/114118 ]· [Model Breach: Anomalous Connection / Application Protocol on Uncommon Port 46% –– Breach URI: /#modelbreach/114113 ] · [Model Breach: Anomalous Connection / New User Agent to IP Without Hostname 62% –– Breach URI: /#modelbreach/114114 ]· [Model Breach: Device / New User Agent 32% –– Breach URI: /#modelbreach/114117 ]· [Model Breach: Anomalous File / EXE from Rare External Location 61% –– Breach URI: /#modelbreach/114122 ]· [Model Breach: Security Integration / Low Severity Integration Detection 54% –– Breach URI: /#modelbreach/114310 ]
[Model Breach: Security Integration / Integration Ransomware Detected 65% –– Breach URI: /#modelbreach/114662 ]Darktrace/Respond Model Breaches
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious File Block 61% –– Breach URI: /#modelbreach/114033 ]
[Model Breach: Antigena / Network::External Threat::Antigena File then New Outbound Block 100% –– Breach URI: /#modelbreach/114038 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block 100% –– Breach URI: /#modelbreach/114040 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block 87% –– Breach URI: /#modelbreach/114041 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach 87% –– Breach URI: /#modelbreach/114043 ]
[Model Breach: Antigena / Network::External Threat::Antigena Ransomware Block 100% –– Breach URI: /#modelbreach/114052 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Significant Security Integration and Network Activity Block 87% –– Breach URI: /#modelbreach/114070 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block 87% –– Breach URI: /#modelbreach/114071 ]
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious Activity Block 87% –– Breach URI: /#modelbreach/114072 ]
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious File Block 53% –– Breach URI: /#modelbreach/114079 ]
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block 64% –– Breach URI: /#modelbreach/114539 ]
[Model Breach: Antigena / Network::External Threat::Antigena Ransomware Block 66% –– Breach URI: /#modelbreach/114667 ]
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious Activity Block 79% –– Breach URI: /#modelbreach/114684 ]·
[Model Breach: Antigena / Network::External Threat::Antigena Ransomware Block 100% –– Breach URI: /#modelbreach/114110 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Significant Anomaly from Client Block 87% –– Breach URI: /#modelbreach/114111 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Controlled and Model Breach 87% –– Breach URI: /#modelbreach/114115 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Breaches Over Time Block 87% –– Breach URI: /#modelbreach/114116 ]·
[Model Breach: Antigena / Network::External Threat::Antigena Suspicious File Block 61% –– Breach URI: /#modelbreach/114121 ]·
[Model Breach: Antigena / Network::External Threat::Antigena File then New Outbound Block 100% –– Breach URI: /#modelbreach/114123 ]·
[Model Breach: Antigena / Network::Significant Anomaly::Antigena Enhanced Monitoring from Client Block 100% –– Breach URI: /#modelbreach/114125 ]

List of IoCs

IoC - Type - Description + Confidence

5.188.87[.]58 - IP address - C2 endpoint

80.66.88[.]145 - IP address - C2 endpoint

/bfyxraav - URI - Possible C2 endpoint URI

/msibfyxraav - URI - Possible C2 endpoint URI

Mozilla/4.0 (compatible; Win32; WinHttp.WinHttpRequest.5) - User agent - Probable user agent leveraged

curl - User agent - Probable user agent leveraged

curl/8.0.1 - User agent - Probable user agent leveraged

Mozilla/4.0 (compatible; Synapse) - User agent - Probable user agent leveraged

Autoit3.exe - Filename - Exe file

CvUYLoTv.au3

eDVeqcCe.au3

FeLlcFRS.au3

FTEZlGhe.au3

HOrzcEWV.au3

rKlArXHH.au3

SjadeWUz.au3

ZgOLxJQy.au3

zSrxhagw.au3

ALOXitYE.au3

DKRcfZfV.au3

gQZVKzek.au3

JZrvmJXK.au3

kLECCtMw.au3

LEXCjXKl.au3

luqWdAzF.au3

mUBNrGpv.au3

OoCdHeJT.au3

PcEJXfIl.au3

ssElzrDV.au3

TcBwRRnp.au3

TFvAUIgu.au3

xkwtvq.au3

otxynh.au3

dcthbq.au3 - Filenames - Possible exe files delivered in response to curl/8.0.1 GET requests with Target URI '/msibfyxraav

f3a0a85fe2ea4a00b3710ef4833b07a5d766702b263fda88101e0cb804d8c699 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

afa3feea5964846cd436b978faa7d31938e666288ffaa75d6ba75bfe6c12bf61 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

63aeac3b007436fa8b7ea25298362330423b80a4cb9269fd2c3e6ab1b1289208 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

ab6704e836a51555ec32d1ff009a79692fa2d11205f9b4962121bda88ba55486 - SHA256 file hash - Possible SHA256 hashes of 'Autoit3.exe' files

References

1. https://www.truesec.com/hub/blog/darkgate-loader-delivered-via-teams

2. https://feedit.cz/wp-content/uploads/2023/03/YiR2022_onepager_ransomware_loaders.pdf

‍3. https://www.virustotal.com/gui/ip-address/5.188.87[.]58

‍4. https://www.forescout.com/resources/darkgate-loader-malspam-campaign/

‍5. https://otx.alienvault.com/indicator/ip/80.66.88[.]145

Written by

Natalia Sánchez Rocafort

Cyber Security Analyst

Inside the SOC

Written by

Natalia Sánchez Rocafort

Cyber Security Analyst

Malware Research Lead

Watch the NIS2 Webinar

Blog

May 28, 2026

From Efficiency to Exposure: How AI Adoption Is Creating Unseen Vulnerabilities on the Factory Floor

How AI agents impact the manufacturing industry

Security teams and IT personnel across the manufacturing industry are under constant pressure to protect production, maintain uptime, and safeguard critical assets but the rise of AI is bringing huge new opportunities alongside new cyber risks. Across manufacturing, AI is embedded into workflows, decision-making, and increasingly, autonomous AI agents are acting on behalf of employees and systems.

Agentic systems are powerful because they can act independently, but that same autonomy also creates cyber and operational risk. Agents have extensive permissions and are capable of carrying out complex tasks, making decisions, and interacting with tools or external systems with little to no human intervention.

Unlike traditional AI models that perform predefined tasks, AI agents use advanced techniques to mimic human decision-making processes, dynamically adapting to new challenges, making decision and taking action based on their own judgement. They look like employees operationally but lack judgment, ethics, or fear of consequences like humans do. This means they can be easily manipulated by cybercriminals, and an AI agent embedded across an OT network creates threats that extend well beyond data exposure. For example, at BMW, AI identifies faults in welding processes as they occur. At its Spartanburg plant, AI monitors the weld of 300-400 metal studs onto every SUV frame to detect misplaced or faulty studs and correct them instantly. Corruption of BMW’s AI system could lead to catastrophic quality control errors.

Adopting agentic AI systems across manufacturing raises some concerns across security teams. New data from our State of AI Cybersecurity survey shows that 78% of manufacturing security professionals are worried about employee use of AI agents – their top concern. That’s followed by employee use of generative AI tools like CoPilot and ChatGPT, a worry for 76% of security professionals at manufacturing organizations. As these tools gain more access to business data and processes, and more autonomy within organizations, security teams, who today have minimal visibility of agent activity in their environments, increasingly have sensitive data exposure (a worry for 60%) and accidental policy and regulatory violations (59%) on their minds.

External AI-powered threats are evolving just as quickly

The same capabilities transforming manufacturing are also reshaping cyberattacks.

AI is enabling attackers to automate reconnaissance, refine targeting, and adapt in real time. What once required time and manual effort can now be executed continuously and at scale. Manufacturers are already seeing the impact. According to manufacturing security professionals we surveyed, 76% are already being impacted by AI-powered threats and 90% see AI increasing the success of social engineering attacks.

And the techniques themselves are evolving. Concerns across the manufacturing sector show growing anxiety about the range of AI-powered attack routes, most pressingly of adaptive malware that evolves in real-time – a prospect half (49%) of manufacturing security professionals we surveyed are worried by, a full 9% more than the average across industries. AI adaptive malware is followed by:

Automated vulnerability scanning and exploit chaining (48%) which has become even more pressing as Anthropic’s new Mythos AI Model supercharges vulnerability discovery

Hyper-personalized phishing campaigns (46%), which remain a mainstay in hackers’ arsenals, and AI has amplified their effectiveness by making phishing emails more convincing and harder to detect.

This is not just an increase in volume, it is a shift toward threats that evolve as they unfold - often faster than static defenses can respond.

Despite rising awareness, many manufacturers are not yet equipped to manage this shift. More than half (51%) say they are not adequately prepared for AI-driven threats, and only 37% have formal policies governing AI deployment.

Securing AI through visibility, context, and guardrails

Addressing this challenge does not require manufacturers to slow innovation. It requires a different approach to security, one that can operate at the same speed and scale as AI. Three specific priorities are emerging for manufacturers looking to take advantage of the power of AI.

Visibility is foundational.

Organizations need to understand where AI is being used, what it can access, and how it behaves across both IT and OT environments. Without that, risk cannot be measured or managed. It is no surprise that Darktrace’s research found that 91% of manufacturing security professionals said that they need to understand how AI makes decisions before trusting it. This is even more critical in operational settings where disruption has safety, environmental, financial, and reputational impacts.

Context is what turns visibility into action.

In environments shaped by AI, normal behavior is constantly shifting. Detecting threats requires a behavioral approach; understanding patterns of life across the organization and identifying subtle deviations in real time – a step change in organizations’ traditional approach to security and risk management.

Guardrails ensure that agency does not become exposure

As AI systems take on greater responsibility, organizations need clear boundaries around what they can do and when they can act independently. These controls must be embedded into systems themselves, not applied after the fact.

Securing AI Agents Across Manufacturing IT and OT

The rise of agentic AI is transforming manufacturing - powering next-generation operations while reshaping the security landscape. This is not just an increase in threats, but a shift to autonomous systems, continuously evolving behaviors, and risks moving at machine speed. For organizations trying to grapple with the challenge of enabling AI while managing the risk, visibility, context and guardrails should be foundational.

Darktrace helps manufacturers build secure AI approaches by making those foundations possible. It provides visibility and real-time detection and response to unusual activity across IT and OT environments and allows organizations to understand AI activity from the prompts employees use and the agents they build to how those agents are behaving across the environment. For manufacturers scaling AI, this delivers a foundation for innovation without sacrificing control.

About the author

Oakley Cox

Director of Product

Blog

May 28, 2026

How to Evaluate AI Vendors: 5 Key categories for AI Adoption

Understanding the AI buyers’ market

AI adoption has become a central topic of discussion in boardrooms, drawing growing interest from business leaders. Ultimately, organizations hope that an investment in AI technology will have tremendous returns. However, the process of buying an AI solution is not as straight forward as it appears on the surface.

While business leaders may be eager to improve productivity across their operations, practitioners responsible for evaluating and selecting AI solutions may not always have the visibility or technical understanding needed to make the right decisions for their business. What is typically marketed as a holistic solution to their most critical problems is usually followed by uncertainty when AI tools are finally operationalized in real environments.

This guide is intended to support security leaders who are under growing pressure to adopt AI tools while navigating complex terminology, vendor claims, and increasingly crowded buying cycles. Ultimately, the goal is to help organizations evaluate and adopt AI in a safe, effective, and well-governed way. To support this, we’ve structured the evaluation framework across five key categories:

Governance, safety, and data controls

Data gathering and training

Model and technique choice

Performance and accuracy validation

Interpretability, adjustability, and transparency

What buying AI looks like in cybersecurity

While investing in AI can bring immense benefits to your security team, first-time buyers of AI cybersecurity solutions may not know where to start. They will have to determine the type of tool they want, know the options available, and evaluate vendors. Research and understanding are critical to ensure purchases are worth the investment.

With acceleration in AI adoption, accompanied by the recent boom in agentic AI and autonomous agents, CISOs must look “beneath the hood" of these tools to understand how they work, how they are governed, and to ensure the system is secure and compliant with internal policies.

Challenges in the AI buyers’ marketplace

The AI security software market is buzzing with hype and flashy promises, which, understandably, needs to be addressed with due diligence. Potential buyers, especially in the cybersecurity space, are hesitant when it comes to allowing AI autonomous capabilities across their workflows, and a lack of vendor transparency can exacerbate those feelings.

Reinforcing this sentiment, research from this year's Darktrace’s State of AI Cybersecurity report shows where confidence and hesitancy emerge amongst potential buyers. On the one hand, security professionals agree that they have good visibility into the logic and reasoning processes their AI solutions use. However, they lack the explainability and trust to allow AI to take independent remedial action.

89% say they have good visibility into the reasoning behind the outputs generated by AI solutions

92% say they need to understand how a defensive AI tool makes decisions before they can trust it

Only 14% say they allow AI to act independently, performing autonomous actions without human approval

74% say they are limiting the autonomy of AI taking action in their SOC until explainability improves

Given the desire for trust and explainability we are seeing from buyers, it's important for them to be equipped with the right questions to ask vendors during an assessment or POV of AI tools in order to demystify marketing hype from real operational outcomes.

Below is a list of categories in which buyers can assess AI vendors or AI Service Providers (AISPs) to help reach safe adoption and maximize their ROI.

5 categories of AI vendor assessment

Darktrace groups these AI-related questions into 5 categories: governance, data and training, model and technique choice, performance validation, and interpretability and adjustability. By asking questions regarding each of these 5 categories, buyers can gain a deeper understanding of how an AISP’s systems work and whether they suit their business requirements.

Governance, safety, and data controls

Governance of AI systems is critical for all AISPs. Whether their platform is based around a single model, or is a more complex, composite AI solution, strong governance is essential to ensure the system is safe, robust, and reliable.

A simple question you could ask is: ‍

What AI governance policies and frameworks do you follow, and/or certifications do you currently maintain?

For more questions you can ask vendors, download the full guide here.

Darktrace is certified to the ISO/IEC 42001 standard, the world’s first AI Management System (AIMS) standard. ISO/IEC 42001 addresses the unique ethical and technical challenges AI poses by setting out a structured way to manage risks such as transparency, accuracy, and misuse. This includes a commitment to ethical AI development, and effective management and monitoring of AI systems both prior to and continually after release.

Data gathering and training

Accurate, meaningful, and unbiased data gathering is the first important step in producing any AI system. An AI model trained using inaccurate, unbalanced, or poor-quality training data will fail to perform optimally.

To alleviate concerns regarding training data quality, a question you could ask is:

‍What steps do you take to prevent bias in your AI models and training data?

For more questions, download the full guide here.

AISPs should be able to provide information about the steps taken, workflows followed, and auditing performed to reduce AI bias where appropriate. While it’s sometimes impossible to fully remove bias from an AI model, appropriate actions should be taken to mitigate or reduce bias where relevant.

Model and technique choice

Different AI techniques are optimal for different tasks. For example, research from Gartner suggests that relying on a single “one-size-fits-all" model can lead to data gaps, especially in highly specialized domains.

To achieve more accurate and robust AI solutions, AI leaders should move beyond using just one model or technique, embrace composite AI practices, and adopt a holistic AI system perspective.

A straightforward question you could ask is simply:

‍What type(s) of AI model(s) do you utilize in your solution?

For more questions, download the full guide here.

While specific detailed information about custom systems used by AISPs is likely proprietary, buyers should expect vendors to be able to provide an overview of the broad techniques used. This will allow you as a buyer to determine if the type of model is appropriate for your use case.

Performance and accuracy validation

Testing and evaluation of performance is essential for all AI systems. Performance analysis should be performed both before release and continually after release to identify potential data or model drift.

A question you could ask to understand an AISPs testing workflow is:

‍How do you audit, test, evaluate, verify, and validate your AI model outputs?

For more questions, download the full guide here.

Testing workflows will likely vary depending on the type of model – measurements relevant to one system may not always be relevant to others. Assessment of systems should also extend beyond these standard accuracy and robustness tests, and should also feature physical performance, such as latency and resource consumption.

Interpretability, adjustability, and transparency

AI systems are typically a black box, simply providing an output without an explanation of how that output was attained. Interpretability and transparency are critical to ensure that both SOC teams and end-users trust the outputs of a system to be accurate and meaningful.

A question you could ask is:

‍How do you promote a trust relationship between human analysts and AI outputs?

For more questions, download the full guide here.

In the context of cybersecurity, trust and interpretability are even more essential. This is particularly relevant for generative AI-based systems (including most AI Agents), where the risk of hallucination can reduce trust in responses.

Cybersecurity systems often need to perform autonomous actions to block incoming threats – an email filtering system may hold potentially dangerous emails; a firewall may block malicious inbound connections. If SOC teams can’t trust these systems to perform accurately, these systems may be limited or disabled, critically reducing their defensive power.

Darktrace as an AI-native cybersecurity vendor

Darktrace has been building and applying AI in cybersecurity for over a decade, developing its capabilities alongside an increasingly complex and fast‑moving threat landscape. This experience has resulted in a mature, multi-layered approach to AI, which continuously learns the normal patterns of each organization to understand behavior, interpret context, and identify meaningful deviations — without relying on predefined rules or known attack signatures. Over time, this has enabled a proven behavioral understanding that helps uncover subtle signals of risk that may otherwise be missed.

With the backing of our ISO/IEC 42001 certification, stakeholders, customers, and partners can be confident that Darktrace is responsibly, ethically, and safely developing its AI systems, and managing the use of AI in day-to-day operations in a compliant and secure manner.

Explore the principles behind Darktrace’s responsible AI approach, informed by collaboration with global experts in academia and governments, detailing how accountability, explainability, and continuous validation are built into its cybersecurity technology.

How Darktrace secures AI systems

Darktrace now brings these capabilities to monitor and respond to risk generated from AI systems across organizations with Darktrace / SECURE AI. This solution analyzes how prompts, agents, and systems are used within the context of each organization, bringing every AI interaction into a single view. This unique approach helps teams understand intent, assess risk, protect sensitive data, and enforce policy across both human and AI agent activity.

Stay up to date

Sign up for the Secure AI Readiness Program here: This gives you exclusive access to the latest news on the latest AI threats, updates on emerging approaches shaping AI security, and insights into the latest innovations, including Darktrace’s ongoing work in this area.

Ready to talk with a Darktrace expert on securing AI? Register here to receive practical guidance on the AI risks that matter most to your business, paired with clarity on where to focus first across governance, visibility, risk reduction, and long-term readiness.

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Conclusion