Our Annual Survey Reveals How Security Teams Are Adapting to AI-Powered Threats
Artificial intelligence is changing the cybersecurity field as fast as any other, both on the offensive and defensive side. We surveyed over 1,500 cybersecurity professionals from around the world to uncover their attitudes, understanding, and priorities when it comes to AI cybersecurity in 2025. Our annual report unearthed some telling trends, and is available now.
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
Max Salisbury
Director, Digital Experience
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04
Mar 2025
At the end of 2023, over half of cybersecurity professionals (60%) reported feeling unprepared for the reality of AI-augmented cyber threats. Twelve months later, that number had dropped to 45%—a clear sign that the industry has recognized the urgency of AI-driven threats and is taking steps to prepare.
This preparation has involved enhancing and optimizing technology and processes in the SOC, improving cybersecurity awareness training, and improving integration among existing cybersecurity solutions. But the biggest priority in addressing the challenge posed by AI-powered cyber-threats, according to the more than 1,500 cybersecurity professionals we surveyed around the world, is defenders themselves adopting defensive AI to fight fire with fire.
In December 2023, 58% listed ‘adding AI-powered security tools to supplement existing solutions’ as a top priority for their teams. By December 2024, it had risen to 64%.
On the other end of the spectrum, ‘increasing security staff’ fell to just over 10% – and only 8% among CISOs. This is despite ‘insufficient personnel’ being listed as the top challenge which inhibits organizations in the fight against AI-powered cyber-threats. This underscores a stark reality: while teams are understaffed and struggling, hiring the right talent is so challenging that expanding headcount is often seen as an unrealistic solution.
What security leaders are looking for in AI-powered solutions
As AI adoption accelerates, confidence in AI-powered security tools remains high, with over 95% of respondents agreeing that AI-enhanced solutions improve their ability to combat advanced threats. But what exactly are security leaders prioritizing when evaluating vendors?
Three key principles emerged:
Platform solutions over point products – 88% of respondents prefer integrated security platforms over standalone tools, emphasizing the need for cohesive and streamlined defense strategies.
A shift toward proactive security – 87% favor solutions that free up security teams to focus on proactive risk management, rather than reacting to attacks after they occur.
Keeping data in-house – 84% express a strong preference for security tools that retain sensitive data within their organization, rather than relying on cloud-hosted ‘data lakes’ for analysis.
The knowledge delta: AI knowledge is growing, but there is a long way to go
While AI adoption is accelerating, how well do security leaders understand the AI technologies they are deploying? Do they have the expertise to differentiate between effective solutions and vague marketing claims?
Our survey found that overall familiarity with AI techniques is improving, particularly with generative AI, which saw the most significant increase in understanding over the past year. Respondents also reported growing awareness of supervised machine learning, Generative Adversarial Networks (GANs), deep learning, and natural language processing. However, knowledge of unsupervised machine learning—critical for identifying novel threats—actually declined.
Alarmingly, 56% of respondents admitted they do not fully understand the AI techniques used in their existing security stack. Clearly there is a long way to go in understanding this vast and fast-changing landscape. Darktrace has recently published a whitepaper breaking down the different AI types in use in cybersecurity which you can read here.
For many security leaders, staying ahead starts with understanding industry trends: how CISOs are thinking about AI’s impact, the steps they are taking, and the challenges they face. Our full State of AI Cybersecurity report is now available, offering deeper insights into these trends across industries, regions, company sizes, and job roles.
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.
Darktrace's Cyber AI Analyst in Action: 4 Real-World Investigations into Advanced Threat Actors
As AI reshapes the cybersecurity landscape, Darktrace’s Cyber AI Analyst automates early-stage investigations, mimicking human reasoning to detect and respond to threats at machine speed. This blog explores four real-world cases where it identified sophisticated threat actors, including nation-state adversaries.
Introducing the AI Maturity Model for Cybersecurity
The AI Maturity Model for Cybersecurity is the most detailed guide of its kind, grounded in real use cases and expert insight. It empowers CISOs to make strategic decisions, not just about what AI to adopt, but how to do it in a way that strengthens their organization over time and achieves successful outcomes.
Introducing Version 2 of Darktrace’s Embedding Model for Investigation of Security Threats (DEMIST-2)
Learn how Darktrace’s DEMIST-2 embedding model delivers high-accuracy threat classification and detection across any environment, outperforming larger models with efficiency and precision.
The benefits of bringing together network and email security
In many organizations, network and email security operate in isolation. Each solution is tasked with defending its respective environment, even though both are facing the same advanced, multi-domain threats.
This siloed approach overlooks a critical reality: email remains the most common vector for initiating cyber-attacks, while the network is the primary stage on which those attacks progress. Without direct integration between these two domains, organizations risk leaving blind spots that adversaries can exploit.
A modern security strategy needs to unify email and network defenses, not just in name, but in how they share intelligence, conduct investigations, and coordinate response actions. Let’s take a look at how this joined-up approach delivers measurable technical, operational, and commercial benefits.
Technical advantages
Pre-alert intelligence: Gathering data before the threat strikes
Most security tools start working when something goes wrong – an unusual login, a flagged attachment, a confirmed compromise. But by then, attackers may already be a step ahead.
By unifying network and email security under a single AI platform (like the Darktrace Active AI Security Platform), you can analyze patterns across both environments in real time, even when there are no alerts. This ongoing monitoring builds a behavioral understanding of every user, device, and domain in your ecosystem.
That means when an email arrives from a suspicious domain, the system already knows whether that domain has appeared on your network before – and whether its behavior has been unusual. Likewise, when new network activity involves a domain first spotted in an email, it’s instantly placed in the right context.
This intelligence isn’t built on signatures or after-the-fact compromise indicators – it’s built on live behavioral baselines, giving your defenses the ability to flag threats before damage is done.
Alert-related intelligence: Connecting the dots in real time
Once an alert does fire, speed and context matter. The Darktrace Cyber AI Analyst can automatically investigate across both environments, piecing together network and email evidence into a single, cohesive incident.
Instead of leaving analysts to sift through fragmented logs, the AI links events like a phishing email to suspicious lateral movement on the recipient’s device, keeping the full attack chain intact. Investigations that might take hours – or even days – can be completed in minutes, with far fewer false positives to wade through.
This is more than a time-saver. It ensures defenders maintain visibility after the first sign of compromise, following the attacker as they pivot into network infrastructure, cloud services, or other targets. That cross-environment continuity is impossible to achieve with disconnected point solutions or siloed workflows.
Operational advantages
Streamlining SecOps across teams
In many organizations, email security is managed by IT, while network defense belongs to the SOC. The result? Critical information is scattered between tools and teams, creating blind spots just when you need clarity.
When email and network data flow into a single platform, everyone is working from the same source of truth. SOC analysts gain immediate visibility into email threats without opening another console or sending a request to another department. The IT team benefits from the SOC’s deeper investigative context.
The outcome is more than convenience: it’s faster, more informed decision-making across the board.
Reducing time-to-meaning and enabling faster response
A unified platform removes the need to manually correlate alerts between tools, reducing time-to-meaning for every incident. Built-in AI correlation instantly ties together related events, guiding analysts toward coordinated responses with higher confidence.
Instead of relying on manual SIEM rules or pre-built SOAR playbooks, the platform connects the dots in real time, and can even trigger autonomous response actions across both environments simultaneously. This ensures attacks are stopped before they can escalate, regardless of where they begin.
Commercial advantages
While purchasing “best-of-breed" for all your different tools might sound appealing, it often leads to a patchwork of solutions with overlapping costs and gaps in coverage. However good a “best-in-breed" email security solution might be in the email realm, it won't be truly effective without visibility across domains and an AI analyst piecing intelligence together. That’s why we think “best-in-suite" is the only “best-in-breed" approach that works – choosing a high-quality platform ensures that every new capability strengthens the whole system.
On top of that, security budgets are under constant pressure. Managing separate vendors for email and network defense means juggling multiple contracts, negotiating different SLAs, and stitching together different support models.
With a single provider for both, procurement and vendor management become far simpler. You deal with one account team, one support channel, and one unified strategy for both environments. If you choose to layer on managed services, you get consistent expertise across your whole security footprint.
Even more importantly, an integrated AI platform sets the stage for growth. Once email and network are under the same roof, adding coverage for other attack surfaces – like cloud or identity – is straightforward. You’re building on the same architecture, not bolting on new point solutions that create more complexity.
Unpacking the Salesloft Incident: Insights from Darktrace Observations
Introduction
On August 26, 2025, Google Threat intelligence Group released a report detailing a widespread data theft campaign targeting the sales automation platform Salesloft, via compromised OAuth tokens used by the third-party Drift AI chat agent [1][2]. The attack has been attributed to the threat actor UNC6395 by Google Threat Intelligence and Mandiant [1].
The attack is believed to have begun in early August 2025 and continued through until mid-August 2025 [1], with the threat actor exporting significant volumes of data from multiple Salesforce instances [1]. Then sifting through this data for anything that could be used to compromise the victim’s environments such as access keys, tokens or passwords. This had led to Google Threat Intelligence Group assessing that the primary intent of the threat actor is credential harvesting, and later reporting that it was aware of in excess of 700 potentially impacted organizations [3].
Salesloft previously stated that, based on currently available data, customers that do not integrate with Salesforce are unaffected by this campaign [2]. However, on August 28, Google Threat Intelligence Group announced that “Based on new information identified by GTIG, the scope of this compromise is not exclusive to the Salesforce integration with Salesloft Drift and impacts other integrations” [2]. Google Threat Intelligence has since advised that any and all authentication tokens stored in or connected to the Drift platform be treated as potentially compromised [1].
This campaign demonstrates how attackers are increasingly exploiting trusted Software-as-a-Service (SaaS) integrations as a pathway into enterprise environment.
By abusing these integrations, threat actors were able to exfiltrate sensitive business data at scale, bypassing traditional security controls. Rather than relying on malware or obvious intrusion techniques, the adversaries leveraged legitimate credentials and API traffic that resembled legitimate Salesforce activity to achieve their goals. This type of activity is far harder to detect with conventional security tools, since it blends in with the daily noise of business operations.
The incident underscores the escalating significance of autonomous coverage within SaaS and third-party ecosystems. As businesses increasingly depend on interconnected platforms, visibility gaps become evident that cannot be managed by conventional perimeter and endpoint defenses.
By developing a behavioral comprehension of each organization's distinct use of cloud services, anomalies can be detected, such as logins from unexpected locations, unusually high volumes of API requests, or unusual document activity. These indications serve as an early alert system, even when intruders use legitimate tokens or accounts, enabling security teams to step in before extensive data exfiltration takes place
What happened?
The campaign is believed to have started on August 8, 2025, with malicious activity continuing until at least August 18. The threat actor, tracked as UNC6395, gained access via compromised OAuth tokens associated with Salesloft Drift integrations into Salesforce [1]. Once tokens were obtained, the attackers were able to issue large volumes of Salesforce API requests, exfiltrating sensitive customer and business data.
Initial Intrusion
The attackers first established access by abusing OAuth and refresh tokens from the Drift integration. These tokens gave them persistent access into Salesforce environments without requiring further authentication [1]. To expand their foothold, the threat actor also made use of TruffleHog [4], an open-source secrets scanner, to hunt for additional exposed credentials. Logs later revealed anomalous IAM updates, including unusual UpdateAccessKey activity, which suggested attempts to ensure long-term persistence and control within compromised accounts.
Internal Reconnaissance & Data Exfiltration
Once inside, the adversaries began exploring the Salesforce environments. They ran queries designed to pull sensitive data fields, focusing on objects such as Cases, Accounts, Users, and Opportunities [1]. At the same time, the attackers sifted through this information to identify secrets that could enable access to other systems, including AWS keys and Snowflake credentials [4]. This phase demonstrated the opportunistic nature of the campaign, with the actors looking for any data that could be repurposed for further compromise.
Lateral Movement
Salesloft and Mandiant investigations revealed that the threat actor also created at least one new user account in early September. Although follow-up activity linked to this account was limited, the creation itself suggested a persistence mechanism designed to survive remediation efforts. By maintaining a separate identity, the attackers ensured they could regain access even if their stolen OAuth tokens were revoked.
Accomplishing the mission
The data taken from Salesforce environments included valuable business records, which attackers used to harvest credentials and identify high-value targets. According to Mandiant, once the data was exfiltrated, the actors actively sifted through it to locate sensitive information that could be leveraged in future intrusions [1]. In response, Salesforce and Salesloft revoked OAuth tokens associated with Drift integrations on August 20 [1], a containment measure aimed at cutting off the attackers’ primary access channel and preventing further abuse.
How did the attack bypass the rest of the security stack?
The campaign effectively bypassed security measures by using legitimate credentials and OAuth tokens through the Salesloft Drift integration. This rendered traditional security defenses like endpoint protection and firewalls ineffective, as the activity appeared non-malicious [1]. The attackers blended into normal operations by using common user agents and making queries through the Salesforce API, which made their activity resemble legitimate integrations and scripts. This allowed them to operate undetected in the SaaS environment, exploiting the trust in third-party connections and highlighting the limitations of traditional detection controls.
Darktrace Coverage
Anomalous activities have been identified across multiple Darktrace deployments that appear associated with this campaign. This included two cases on customers based within the United States who had a Salesforce integration, where the pattern of activities was notably similar.
On August 17, Darktrace observed an account belonging to one of these customers logging in from the rare endpoint 208.68.36[.]90, while the user was seen active from another location. This IP is a known indicator of compromise (IoC) reported by open-source intelligence (OSINT) for the campaign [2].
Figure 1: Cyber AI Analyst Incident summarizing the suspicious login seen for the account.
The login event was associated with the application Drift, further connecting the events to this campaign.
Figure 2: Advanced Search logs showing the Application used to login.
Following the login, the actor initiated a high volume of Salesforce API requests using methods such as GET, POST, and DELETE. The GET requests targeted endpoints like /services/data/v57.0/query and /services/data/v57.0/sobjects/Case/describe, where the former is used to retrieve records based on a specific criterion, while the latter provides metadata for the Case object, including field names and data types [5,6].
Subsequently, a POST request to /services/data/v57.0/jobs/query was observed, likely to initiate a Bulk API query job for extracting large volumes of data from the Ingest Job endpoint [7,8].
Finally, a DELETE request to remove an ingestion job batch, possibly an attempt to obscure traces of prior data access or manipulation.
A case on another US-based customer took place a day later, on August 18. This again began with an account logging in from the rare IP 208.68.36[.]90 involving the application Drift. This was followed by Salesforce GET requests targeting the same endpoints as seen in the previous case, and then a POST to the Ingest Job endpoint and finally a DELETE request, all occurring within one minute of the initial suspicious login.
The chain of anomalous behaviors, including a suspicious login and delete request, resulted in Darktrace’s Autonomous Response capability suggesting a ‘Disable user’ action. However, the customer’s deployment configuration required manual confirmation for the action to take effect.
Figure 3: An example model alert for the user, triggered due to an anomalous API DELETE request.
Figure 4: Model Alert Event Log showing various model alerts for the account that ultimately led to an Autonomous Response model being triggered.
Conclusion
In conclusion, this incident underscores the escalating risks of SaaS supply chain attacks, where third-party integrations can become avenues for attacks. It demonstrates how adversaries can exploit legitimate OAuth tokens and API traffic to circumvent traditional defenses. This emphasizes the necessity for constant monitoring of SaaS and cloud activity, beyond just endpoints and networks, while also reinforcing the significance of applying least privilege access and routinely reviewing OAuth permissions in cloud environments. Furthermore, it provides a wider perspective into the evolution of the threat landscape, shifting towards credential and token abuse as opposed to malware-driven compromise.
Credit to Emma Foulger (Global Threat Research Operations Lead), Calum Hall (Technical Content Researcher), Signe Zaharka (Principal Cyber Analyst), Min Kim (Senior Cyber Analyst), Nahisha Nobregas (Senior Cyber Analyst), Priya Thapa (Cyber Analyst)
Appendices
Darktrace Model Detections
· SaaS / Access / Unusual External Source for SaaS Credential Use
· SaaS / Compromise / Login From Rare Endpoint While User Is Active
· SaaS / Compliance / Anomalous Salesforce API Event
Customers should consider integrating Salesforce with Darktrace where possible. These integrations allow better visibility and correlation to spot unusual behavior and possible threats.