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March 20, 2024

How Phishing Attacks Are Becoming Harder to Identify

Learn about the cyber risks posed by advanced phishing attacks and how AI can enhance security solutions to defend against them.
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.
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The Darktrace Community
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20
Mar 2024

The state of email security and phishing attacks

Employees send and receive hundreds of emails a day to keep businesses moving. Unfortunately, it just takes one employee to interact with an undetected phishing email to potentially put an entire organization at risk from cyber disruption. Attackers know this, which is why they continue to develop and improve email phishing attacks.  

Increased attack sophistication makes it harder than ever for traditional cyber security solutions like SEGs, firewalls, and spam filters to detect and mitigate increasingly novel and sophisticated email threats.

When there are tell-tale signs of a threat, these solutions can  identify an incoming message as suspicious. Pointers such as emails from unknown senders, messages which contain an unusual amount of poor spelling and grammar or encourage the receiver to respond to an unexpected but supposedly urgent request.

That is, if the phishing attacks weren’t blocked by security measures before reaching the victim’s inbox. But, this is happening more and more often as phishing campaigns are becoming more advanced. Attackers are showing signs of consistently bypassing traditional protections and getting through to exploit victims.  

Darktrace email threat reporting

In its End of Year Threat Report, Darktrace analyzed over 10 million phishing emails targeting customer environments between September 1 and December 31, 2023.  Our findings signal that attackers are starting to take advantage of advancements in artificial intelligence (AI), including using Generative AI tools such as Large Language Models (LLMs) to create more convincing and sophisticated phishing messages – and at scale.

LLMs and Phishing

With the right AI prompts, attackers can use these LLMs to help write convincing email messages designed to target specific countries, companies or even individuals – all without the suspicious hallmarks which are traditionally associated with standard phishing attacks. The attackers don’t even need to speak the language of the individuals or groups they’re targeting.  LLMs lower language barriers for attackers; using their native tongue, they can simply ask the Generative AI to write a message in the language of their choosing.  

These techniques are designed to build trust and manipulate recipients into giving up sensitive information like user credentials, intellectual property or bank information or coerce them into downloading malicious payloads which can be used to launch further attacks on business infrastructure.  With the appropriate research, attackers can tailor the messages to increase the chances of being successful, like making them look like a legitimate company email or request.

Social engineering phishing attacks

A year ago. Darktrace shared research which found a 135% increase in ‘novel social engineering attacks’ in the first two months of 2023, corresponding with the widespread adoption of ChatGPT. These novel phishing attacks showed a strong linguistic deviation compared to other phishing emails, which suggested to us that Generative AI was already providing an avenue for threat actors to craft sophisticated and targeted attacks at speed and scale

We’ve seen this trend continue. Our End of Year Threat Report found 38% of these emails were identified as utilizing novel social engineering techniques.

Attackers are also deploying another technique to make phishing emails look more convincing – they’re making the emails themselves longer and more sophisticated.  

A potential victim might be suspicious of an ‘urgent’ email which prompts them to take action without an explanation - but if there’s additional context in the text, it adds an aura of legitimacy which is difficult to act against.

And threat actors know this; 28% of phishing emails analyzed by Darktrace over the period were identified as having “significant” amount of text – containing over 1,000 characters, which equates to over 200 words.  

It’s a sign that attackers are innovating and bolstering their efforts to craft sophisticated phishing campaigns, potentially leveraging Generative AI tools to automate social engineering activity by creating longer, more convincing phishing emails.  

QR code phishing

But this is far from the only innovative method which attackers are using to bypass traditional security defences. Among the 10 million plus emails analyzed during the reporting period, Darktrace/Email detected over 639,000 malicious QR codes within the messages.

Malicious QR codes placed within emails have become an increasingly common form of phishing attack, especially as QR codes have become a more common method for sharing links to information or buying links for products in recent years.

Attackers are deploying QR codes because they provide a way of directing unsuspecting victims to malicious websites or download links without needing to use a traditional phishing URL.  

The advantage of implanting QR codes for attackers is that while phishing URLs are something which traditional security solutions are actively looking to identify and mitigate, malicious QR codes are more difficult for them to detect.

Applying AI to email security

Traditional security solutions which rely heavily on previously identified malicious emails and known bad senders are struggling to identify and defend against these novel and increasingly sophisticated email threats.

But by using AI that learns the unique digital environment and patterns of each business, Darktrace/Email can recognize the subtle deviations in expected email activity to determine whether any given email could represent a threat to the business. It is then able to make highly accurate decisions to mitigate and neutralize any email attack it faces helping to keep your organization safe from cyber disruption.

It’s therefore imperative that in the battle against ever-evolving, ever more sophisticated cyber threats, defenders are also embracing AI to keep businesses safe. By effectively applying AI to cyber security challenges, defenders can take a proactive approach to cyber security, staying one step ahead of malicious attackers, with real-time detection and automated response to known and unknown threats looking to disrupt the business via the inbox.  

Darktrace/Email was recently awarded a 2024 AI Excellence Award for Machine Learning by Business Intelligence Group.

Join Darktrace on 9 April for a virtual event to explore the latest innovations needed to get ahead of the rapidly evolving threat landscape. Register today to hear more about our latest innovations coming to Darktrace’s offerings.

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

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June 1, 2026

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

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

They don’t break in. They blend in.

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

Confidence is creating risk

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

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

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

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

Attackers anticipate what we miss

Even well-trained users can become entry points.

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

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

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

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

The most dangerous threats are already inside

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

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

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

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

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

“Unusual” behavior is the new red flag

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

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

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

AI shifts defense from reaction to anticipation

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

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

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

  • Trusted sessions
  • Legitimate services
  • Human error

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

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

Resilience, not perfection, is the new security standard

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

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

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

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

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May 28, 2026

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

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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.

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About the author
Oakley Cox
Director of Product
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