Blog
/
Network
/
August 3, 2022

The Risks of Remote Access Tools

Discover how remote access tools in exploitations across OT/ICS and corporate environments benefit from Darktrace's product suite.
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
Dylan Hinz
Cyber Analyst
Default blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog imageDefault blog image
03
Aug 2022

Understanding remote access tools

In 2022, remote access tools continue to provide versatile support to organizations. By controlling devices remotely from across the globe, IT teams save on response costs, travel times, and can receive remote support from external parties like contractors [1 & 2]. This is particularly relevant in cases involving specialty machines such as OT/ICS systems where physical access is sometimes limited. These tools, however, come with their own risks. The following blog will discuss these risks and how they can be addressed (particularly in OT environments) by looking at two exploit examples from the popular sphere and within the Darktrace customer base. 

What are remote access tools?

One of the most popular remote tools is TeamViewer, a comprehensive videoconferencing and remote management tool which can be used on both desktop and handheld devices[3]. Like other sophisticated tools, when it works as intended, it can seem like magic. However, remote access tools can be exploited and may grant privileged network access to potential threat actors. Although TeamViewer needs to be installed on both perpetrator and victim devices, if an attacker has access to a misconfigured TeamViewer device, it becomes trivial to establish a foothold and deploy malware. 

How secure is remote access?

Security vulnerabilities in remote access tools

In early 2021, remote access tooling was seen on a new scale against the City of Oldsmar’s water treatment plant [4] (Figure 1). Oldsmar manages chemical concentration levels in the water for a 15,000-person city. The water treatment plant had been using TeamViewer to allow employees to share screens and work through IT issues. However, in February an employee noticed he had lost control of his mouse cursor. Initially he was unconcerned; the employee assumed that the cursor was being controlled by his boss, who regularly connected to the computer to monitor the facility’s systems. A few hours later though, the employee again saw his cursor moving out of his control and this time noticed that it was attempting to change levels of sodium hydroxide in the water supply (which is extremely dangerous for human consumption). Thankfully, the employee was able to quickly spot the changes and return them to their normal level. When looking back at the event, the key question posed by officials was where exactly the vulnerability was located in their security stack. [5]. The answer was unclear.

Photograph of compromised water plant in Florida 
Figure 1: Photograph of compromised water plant in Florida 

Tactics and strategies

When attackers get initial network access, the primary challenge for any enterprise is identifying a) that a device compromise has happened and b) how it happened. These were the same challenges seen in the Oldsmar attack. When the first physical signs of compromise occurred (cursor movement), the impacted user was still unsure whether the activity was malicious. A detailed investigation from Dragos revealed the how: evidence of a watering hole, reconnaissance activity a month prior, a targeted variant of the Tofsee botnet, and the potential presence of two separate threat actors [6 & 7]. The answer to both questions pointed to a complex attack. However, with Darktrace these questions become less important. 

How Darktrace stops compromised remote access

Darktrace does not rely on signatures but instead has AI-based models for live detection of these tools and anomalies within the wider network. Regardless of the security ‘hole’, live detection gives security teams the potential to respond in near-live time.

According to Darktrace’s Chief Product Officer, Max Heinemeyer, the Oldsmar attack was possible because it “Abused off-the-shelf tools that were already used by the client, specifically TeamViewer. This tactic, which targeted the domain controller as the initial vector, made the malware deployment easy and effective.” [8]. 

Darktrace has multiple DETECT models to provide visibility over anomalous TeamViewer or remote access tool usage:

·      Compliance / Incoming Remote Access Tool

·      Compliance / Remote Management Tool On Client

·      Compliance / Remote Management Tool On Server

·      Device / Activity Identifier / Teamviewer 

General incoming privileged connections:

·      Compliance / Incoming Remote Desktop

·      Compliance / Incoming SSH

Industrial DETECT can also highlight any new or unusual changes in ICS/OT systems:

·      ICS / Incoming ICS Command

·      ICS / Incoming RDP And ICS Commands

·      ICS / Uncommon ICS Error

Darktrace gives security teams the opportunity for a proactive response, and it is up to those teams to utilize that opportunity. In recent months our SOC Team have also seen remote access controls being abused for high-profile threats. In one example, Darktrace detected a ransomware attack supported by the installation of AnyDesk. 

Initial detection of compromise

In May a company’s mail server was detected making multiple external requests for an unusual file ‘106.exe’ using a PowerShell agent (6b79549200af33bf0322164f8a4d56a0fa08a5a62ab6a5c93a6eeef2065430ce). Although some requests were directed to sinkholes, many were otherwise successful. Subsequently a DDL file with hash f126ce9014ee87de92e734c509e1b5ab71ffb2d5a8b27171da111f96f3ba0e75 (marked by VirusTotal as malicious) was downloaded. This was followed by the installation of AnyDesk: a remote access tool likely deployed for backdoor purposes during further compromises. It is clear the threat actor then moved on to reconnaissance, with new Mimikatz use and a large volume of ICMP and SMBv.1 scanning sessions using a default credential. DCE-RPC calls were also made to the Netlogon service, suggesting a possible attempt to exploit 2020’s Zerologon vulnerability (CVE-2020-1472) [9]. When the customer then discovered a ransom note pertaining to LV (repurposed REvil), Darktrace analysts helped them to re-configure Darktrace RESPOND and turn it to active rather than human confirmation mode (Figure 2). 

Figure 2: Capture of LV ransom note provided by customer

Whilst in this instance the tool was not used for initial access, it was still an important contingency tool to ensure the threat actor’s persistency as the customer tried to respond to the ongoing breach. Yet it was the visibility provided by Darktrace model detection and changes to RESPOND configuration which ensured the customer kept up with this actor and reduced the impact of the attack. 

Looking back at Oldsmar, it is clear that being aware of remote access tools is only half the battle. More importantly, most organizations are asking if their use in attacks can be prevented in the first place. As an off-the-shelf tool, restricting TeamViewer use seems like an easy solution but such tools are often essential for maintenance and support operations. Even if limited to privileged users, these accounts are also subject to potential compromise. Instead, companies can take a large-scale view and consider the environment in which the Oldsmar attack occurred. 

How IT & OT convergence complicated this attack

In this context, the separation of OT and IT systems is a potential solution - if attackers cannot access at-risk systems, then they also cannot attack those systems. However, with recent discourse around the IT-OT convergence and increased use of IoT devices, this separation is increasingly challenging to implement [10]. Complex networking designs, stringent patching requirements and ever-changing business/operational needs are all big considerations when establishing industrial security. In fact, Tenable’s CEO Amit Yoran encouraged less separation following Oldsmar: “There’s business reasons and efficiency reasons that you might want to connect those to be able to predict when parts are going to fail or when outages are going to occur [sic].” [11]. 

When neither addressing remote access use or industrial set-up provides a quick solution, then security teams need to look to third-party support to stop similar attacks. In addition to Darktrace DETECT, our Darktrace PREVENT range with PREVENT/Attack Surface Management (ASM) can also alert security teams to internet-facing devices at risk of remote access exploitation. ASM actively queries the Shodan API for open ports on company websites and exposed servers. This highlights those assets which might be vulnerable to this type of remote access.   

Conclusion

In conclusion, TeamViewer and other remote access tools offer a lot of convenience for security teams but also for attackers. Attackers can remotely access important systems including those in the industrial network and install malware using remote access tools as leverage. Security teams need to know both their normal authorized activities and how to enforce them. With Darktrace DETECT, the tools are given transparency, with Darktrace RESPOND they can be blocked, and now Darktrace PREVENT/ASM helps to mitigate the risk of attack before it happens. As the professional world continues to embrace hybrid working, it becomes increasingly crucial to embrace these types of products and ensure protection against the dangers of unwanted remote access. 

Thanks to Connor Mooney for his contributions to this blog.

Appendices

References 

[1] https://goabacus.com/advantages-and-disadvantages-of-remote-access-service/ 

[2] https://blog.ericom.com/advantages-of-remote-access/ 

[3] https://www.teamviewer.com/en/documents/ 

[4] https://www.wired.com/story/oldsmar-florida-water-utility-hack/ 

[5 & 11] https://www.bankinfosecurity.com/ot-it-integration-raises-risk-for-water-providers-experts-say-a-18841 

[6] https://www.dragos.com/blog/industry-news/a-new-water-watering-hole/ 

[7] https://www.dragos.com/blog/industry-news/recommendations-following-the-oldsmar-water-treatment-facility-cyber-attack/

[8] https://customerportal.darktrace.com/darktrace-blogs/get-blog/53  

[9] https://www.crowdstrike.com/blog/cve-2020-1472-zerologon-security-advisory/

[10] https://www.mckinsey.com/business-functions/operations/our-insights/converge-it-and-ot-to-turbocharge-business-operations-scaling-power

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
Dylan Hinz
Cyber Analyst

More in this series

No items found.

Blog

/

/

December 22, 2025

The Year Ahead: AI Cybersecurity Trends to Watch in 2026

Default blog imageDefault blog image

Each year, we ask some of our experts to step back from the day-to-day pace of incidents, vulnerabilities, and headlines to reflect on the forces reshaping the threat landscape. The goal is simple:  to identify and share the trends we believe will matter most in the year ahead, based on the real-world challenges our customers are facing, the technology and issues our R&D teams are exploring, and our observations of how both attackers and defenders are adapting.  

In 2025, we saw generative AI and early agentic systems moving from limited pilots into more widespread adoption across enterprises. Generative AI tools became embedded in SaaS products and enterprise workflows we rely on every day, AI agents gained more access to data and systems, and we saw glimpses of how threat actors can manipulate commercial AI models for attacks. At the same time, expanding cloud and SaaS ecosystems and the increasing use of automation continued to stretch traditional security assumptions.

Looking ahead to 2026, we’re already seeing the security of AI models, agents, and the identities that power them becoming a key point of tension – and opportunity -- for both attackers and defenders. Long-standing challenges and risks such as identity, trust, data integrity, and human decision-making will not disappear, but AI and automation will increase the speed and scale of the cyber risk.  

Here's what a few of our experts believe are the trends that will shape this next phase of cybersecurity, and the realities organizations should prepare for.  

Agentic AI is the next big insider risk: In 2026, organizations may experience their first large-scale security incidents driven by agentic AI behaving in unintended ways—not necessarily due to malicious intent, but because of how easily agents can be influenced. AI agents are designed to be helpful, lack judgment, and operate without understanding context or consequence. This makes them highly efficient—and highly pliable. Unlike human insiders, agentic systems do not need to be socially engineered, coerced, or bribed. They only need to be prompted creatively, misinterpret legitimate prompts, or be vulnerable to indirect prompt injection. Without strong controls around access, scope, and behavior, agents may over-share data, misroute communications, or take actions that introduce real business risk. Securing AI adoption will increasingly depend on treating agents as first-class identities—monitored, constrained, and evaluated based on behavior, not intent.

-- Nicole Carignan, SVP of Security & AI Strategy


Prompt Injection Moves from Theory to Front-Page Breach: We’ll see the first major story of an indirect prompt injection attack against companies adopting AI either through an accessible chatbot or an agentic system ingesting a hidden prompt. In practice, this may result in unauthorized data exposure or unintended malicious behavior by AI systems, such as over-sharing information, misrouting communications, or acting outside their intended scope. Recent attention on this risk—particularly in the context of AI-powered browsers and additional safety layers being introduced to guide agent behavior—highlights a growing industry awareness of the challenge.  

-- Collin Chapleau, Senior Director of Security & AI Strategy

Humans are even more outpaced, but not broken: When it comes to cyber, people aren’t failing; the system is moving faster than they can. Attackers exploit the gap between human judgment and machine-speed operations. The rise of deepfakes and emotion-driven scams that we’ve seen in the last few years reduce our ability to spot the familiar human cues we’ve been taught to look out for. Fraud now spans social platforms, encrypted chat, and instant payments in minutes. Expecting humans to be the last line of defense is unrealistic.

Defense must assume human fallibility and design accordingly. Automated provenance checks, cryptographic signatures, and dual-channel verification should precede human judgment. Training still matters, but it cannot close the gap alone. In the year ahead, we need to see more of a focus on partnership: systems that absorb risk so humans make decisions in context, not under pressure.

-- Margaret Cunningham, VP of Security & AI Strategy

AI removes the attacker bottleneck—smaller organizations feel the impact: One factor that is currently preventing more companies from breaches is a bottleneck on the attacker side: there’s not enough human hacker capital. The number of human hands on a keyboard is a rate-determining factor in the threat landscape. Further advancements of AI and automation will continue to open that bottleneck. We are already seeing that. The ostrich approach of hoping that one’s own company is too obscure to be noticed by attackers will no longer work as attacker capacity increases.  

-- Max Heinemeyer, Global Field CISO

SaaS platforms become the preferred supply chain target: Attackers have learned a simple lesson: compromising SaaS platforms can have big payouts. As a result, we’ll see more targeting of commercial off-the-shelf SaaS providers, which are often highly trusted and deeply integrated into business environments. Some of these attacks may involve software with unfamiliar brand names, but their downstream impact will be significant. In 2026, expect more breaches where attackers leverage valid credentials, APIs, or misconfigurations to bypass traditional defenses entirely.

-- Nathaniel Jones, VP of Security & AI Strategy


Increased commercialization of generative AI and AI assistants in cyber attacks: One trend we’re watching closely for 2026 is the commercialization of AI-assisted cybercrime. For example, cybercrime prompt playbooks sold on the dark web—essentially copy-and-paste frameworks that show attackers how to misuse or jailbreak AI models. It’s an evolution of what we saw in 2025, where AI lowered the barrier to entry. In 2026, those techniques become productized, scalable, and much easier to reuse.  

 

-- Toby Lewis, Global Head of Threat Analysis


Taken together, these trends underscore that the core challenges of cybersecurity are not changing dramatically -- identity, trust, data, and human decision-making still sit at the core of most incidents. What is changing quickly is the environment in which these challenges play out. AI and automation are accelerating everything: how quickly attackers can scale, how widely risk is distributed, and how easily unintended behavior can create real impact. And as technology like cloud services and SaaS platforms become even more deeply integrated into businesses, the potential attack surface continues to expand.  

Predictions are not guarantees. But the patterns emerging today suggest that 2026 will be a year where securing AI becomes inseparable from securing the business itself. The organizations that prepare now—by understanding how AI is used, how it behaves, and how it can be misused—will be best positioned to adopt these technologies with confidence in the year ahead.

Learn more about how to secure AI adoption in the enterprise without compromise by registering to join our live launch webinar on February 3, 2026.  

Continue reading
About the author

Blog

/

Email

/

December 18, 2025

Why organizations are moving to label-free, behavioral DLP for outbound email

Man at laptopDefault blog imageDefault blog image

Why outbound email DLP needs reinventing

In 2025, the global average cost of a data breach fell slightly — but remains substantial at USD 4.44 million (IBM Cost of a Data Breach Report 2025). The headline figure hides a painful reality: many of these breaches stem not from sophisticated hacks, but from simple human error: mis-sent emails, accidental forwarding, or replying with the wrong attachment. Because outbound email is a common channel for sensitive data leaving an organization, the risk posed by everyday mistakes is enormous.

In 2025, 53% of data breaches involved customer PII, making it the most commonly compromised asset (IBM Cost of a Data Breach Report 2025). This makes “protection at the moment of send” essential. A single unintended disclosure can trigger compliance violations, regulatory scrutiny, and erosion of customer trust –consequences that are disproportionate to the marginal human errors that cause them.

Traditional DLP has long attempted to mitigate these impacts, but it relies heavily on perfect labelling and rigid pattern-matching. In reality, data loss rarely presents itself as a neat, well-structured pattern waiting to be caught – it looks like everyday communication, just slightly out of context.

How data loss actually happens

Most data loss comes from frustratingly familiar scenarios. A mistyped name in auto-complete sends sensitive data to the wrong “Alex.” A user forwards a document to a personal Gmail account “just this once.” Someone shares an attachment with a new or unknown correspondent without realizing how sensitive it is.

Traditional, content-centric DLP rarely catches these moments. Labels are missing or wrong. Regexes break the moment the data shifts formats. And static rules can’t interpret the context that actually matters – the sender-recipient relationship, the communication history, or whether this behavior is typical for the user.

It’s the everyday mistakes that hurt the most. The classic example: the Friday 5:58 p.m. mis-send, when auto-complete selects Martin, a former contractor, instead of Marta in Finance.

What traditional DLP approaches offer (and where gaps remain)

Most email DLP today follows two patterns, each useful but incomplete.

  • Policy- and label-centric DLP works when labels are correct — but content is often unlabeled or mislabeled, and maintaining classification adds friction. Gaps appear exactly where users move fastest
  • Rule and signature-based approaches catch known patterns but miss nuance: human error, new workflows, and “unknown unknowns” that don’t match a rule

The takeaway: Protection must combine content + behavior + explainability at send time, without depending on perfect labels.

Your technology primer: The three pillars that make outbound DLP effective

1) Label-free (vs. data classification)

Protects all content, not just what’s labeled. Label-free analysis removes classification overhead and closes gaps from missing or incorrect tags. By evaluating content and context at send time, it also catches misdelivery and other payload-free errors.

  • No labeling burden; no regex/rule maintenance
  • Works when tags are missing, wrong, or stale
  • Detects misdirected sends even when labels look right

2) Behavioral (vs. rules, signatures, threat intelligence)

Understands user behavior, not just static patterns. Behavioral analysis learns what’s normal for each person, surfacing human error and subtle exfiltration that rules can’t. It also incorporates account signals and inbound intel, extending across email and Teams.

  • Flags risk without predefined rules or IOCs
  • Catches misdelivery, unusual contacts, personal forwards, odd timing/volume
  • Blends identity and inbound context across channels

3) Proprietary DSLM (vs. generic LLM)

Optimized for precise, fast, explainable on-send decisions. A DSLM understands email/DLP semantics, avoids generative risks, and stays auditable and privacy-controlled, delivering intelligence reliably without slowing mail flow.

  • Low-latency, on-send enforcement
  • Non-generative for predictable, explainable outcomes
  • Governed model with strong privacy and auditability

The Darktrace approach to DLP

Darktrace / EMAIL – DLP stops misdelivery and sensitive data loss at send time using hold/notify/justify/release actions. It blends behavioral insight with content understanding across 35+ PII categories, protecting both labeled and unlabeled data. Every action is paired with clear explainability: AI narratives show exactly why an email was flagged, supporting analysts and helping end-users learn. Deployment aligns cleanly with existing SOC workflows through mail-flow connectors and optional Microsoft Purview label ingestion, without forcing duplicate policy-building.

Deployment is simple: Microsoft 365 routes outbound mail to Darktrace for real-time, inline decisions without regex or rule-heavy setup.

A buyer’s checklist for DLP solutions

When choosing your DLP solution, you want to be sure that it can deliver precise, explainable protection at the moment it matters – on send – without operational drag.  

To finish, we’ve compiled a handy list of questions you can ask before choosing an outbound DLP solution:

  • Can it operate label free when tags are missing or wrong? 
  • Does it truly learn per user behavior (no shortcuts)? 
  • Is there a domain specific model behind the content understanding (not a generic LLM)? 
  • Does it explain decisions to both analysts and end users? 
  • Will it integrate with your label program and SOC workflows rather than duplicate them? 

For a deep dive into Darktrace’s DLP solution, check out the full solution brief.

[related-resource]

Continue reading
About the author
Carlos Gray
Senior Product Marketing Manager, Email
Your data. Our AI.
Elevate your network security with Darktrace AI