The responsibilities placed on cybersecurity leaders are becoming increasingly difficult to manage as organizations face a growing number of cyber threats, rapid adoption of artificial intelligence technologies, and increasing demands for security oversight across the business.
A recent survey conducted by the Information Systems Security Association (ISSA) International and research firm Omdia found that 68% of cybersecurity and IT professionals believe their jobs are more difficult today than they were two years ago. More than half of respondents reported heavier workloads and greater operational complexity (55%), while 52% said the volume and intensity of cyber threats have become more overwhelming.
Security teams are being asked to protect increasingly complex digital environments while also helping organizations adopt new technologies such as generative AI. At the same time, many security leaders say they are struggling to secure sufficient support from other parts of the business.
According to Shawn Murray, former president of ISSA and a fractional Chief Information Security Officer (CISO), many security executives regularly work long hours while attempting to address security concerns that are often introduced without their involvement. In some organizations, new technologies are adopted before security teams are included in planning discussions, creating additional challenges for risk management and governance.
As a result, some experienced CISOs are leaving traditional full-time leadership positions and choosing consulting or fractional roles instead. These arrangements allow security professionals to work with multiple organizations while focusing on businesses that are willing to involve cybersecurity leaders in strategic decision-making.
While legal accountability was once considered one of the largest concerns facing CISOs, the survey suggests that anxiety around personal liability has become less prominent than in previous years. Instead, many respondents identified the security implications of artificial intelligence as one of the most significant new sources of pressure.
AI has created both opportunities and challenges for cybersecurity teams. One growing concern is the rise of "shadow AI," where employees begin using AI tools and services without notifying security teams or obtaining formal approval. Similar issues emerged during the early stages of cloud adoption, when departments could deploy new services independently without providing visibility to cybersecurity staff.
This lack of visibility can create greater security gaps. When security teams do not know which AI applications, models, or processes are being used across an organization, it becomes more difficult to identify risks, monitor suspicious activity, and respond effectively to potential incidents.
Despite these concerns, cybersecurity professionals are increasingly interested in using AI to improve their own operations. The survey found that 37% of respondents are already using AI-powered tools to address cybersecurity challenges, while another 46% plan to adopt such technologies in the future.
Among the most common use cases identified by respondents were automated cybersecurity assessments, software testing, predictive risk analysis, and threat detection. These capabilities could help security teams reduce manual workloads and process large volumes of security data more efficiently.
Alex Hutton, CISO at Atlantic Union Bank, noted that the cybersecurity environment has changed significantly in recent years. Whether organizations fully embrace advanced AI systems or not, security professionals must continuously learn about new technologies, understand emerging risks, and adapt their security strategies accordingly.
The survey also highlighted a notable shift in how organizations obtain cybersecurity leadership. The percentage of companies employing full-time CISOs declined from 76% in 2024 to 63%, while the use of fractional CISOs increased from 6% to 15% over the same period.
Industry observers believe this trend reflects growing demand for cybersecurity expertise rather than a reduction in the importance of the CISO role. Many small and mid-sized organizations face the same security, compliance, and governance challenges as larger enterprises but often lack the budget required to hire a full-time executive.
Cyber insurance requirements are also contributing to demand for experienced security leadership. Organizations are increasingly expected to demonstrate strong cybersecurity practices and effective risk management controls before obtaining coverage or meeting insurer requirements. CISOs frequently play a central role in helping businesses assess risks, improve security programs, and document compliance efforts.
According to Hutton, the rise of fractional and virtual CISOs provides organizations with access to executive-level security guidance without requiring a full-time appointment. Rather than signaling the decline of cybersecurity leadership positions, the change may represent an expansion of cybersecurity services to organizations that previously could not afford dedicated executive expertise.
As cyber threats continue to grow and AI reshapes business operations, cybersecurity leaders are expected to remain critical decision-makers. However, the role itself is changing, requiring security professionals to balance technical oversight, business strategy, regulatory expectations, and emerging technologies in an increasingly demanding environment.
The ransomware operation known as INC has grown into one of the most active cybercrime groups of 2026, with security researchers linking it to more than 830 victims since it first appeared in August 2023.
According to researchers at Acronis, the group's rise coincided with disruptions affecting major ransomware brands such as LockBit and BlackCat. As affiliates sought alternative platforms, INC appears to have benefited from that shift. More than 65% of the victims listed by the group are based in the United States, with legal firms, healthcare providers, manufacturers, construction companies, and technology organizations among the most frequently targeted sectors.
Researchers also observed major changes to the ransomware itself. INC's malware for Windows and Linux/VMware ESXi systems has been rewritten in Rust, a programming language increasingly adopted by malware developers because it supports multiple operating systems and can complicate reverse-engineering efforts.
The group's toolkit has expanded as well. Recent attacks have involved a credential-stealing utility capable of extracting authentication data from newer Veeam backup deployments that use salted DPAPI encryption. Access to backup infrastructure can give attackers valuable credentials while also making recovery efforts more difficult for victims.
Acronis noted that the sale of INC's Windows and Linux ransomware variants on underground cybercrime forums in May 2024 contributed to the appearance of related ransomware families, including Lynx and Sinobi. Researchers identified significant code similarities between the groups.
Investigators found that INC affiliates rely on several entry points to compromise networks, including spear-phishing campaigns, credentials purchased from Initial Access Brokers (IABs), and the exploitation of publicly exposed systems running vulnerable versions of Citrix NetScaler, Fortinet EMS, and SimpleHelp software.
Once inside a network, attackers harvest credentials, move between systems using legitimate administrative tools such as RDP and PsExec, and attempt to weaken security controls through a technique known as Bring Your Own Vulnerable Driver (BYOVD). Researchers observed the use of vulnerable drivers including filwfp.sys, filnk.sys, and fildds.sys. The group also deploys tools such as Cobalt Strike, AnyDesk, ScreenConnect, and TeamViewer to maintain access and control compromised environments.
Before encryption begins, stolen files are collected and transferred using Rclone, often after being packaged into password-protected archives. The ransomware then encrypts systems using multithreading and partial-encryption techniques to speed up the process. When launched against VMware ESXi environments, the malware can also attempt to shut down virtual machines.
Data from ZeroFox ranked INC as the fourth most active ransomware operation during the first quarter of 2026, recording more than 120 incidents. Researchers said the group's growth demonstrates how ransomware operators can build large-scale campaigns using widely available tools, stolen credentials, and unpatched systems rather than relying on highly specialized malware.
![]() |
For years, cybersecurity teams have relied on established methods to determine how dangerous a threat actor might be. Analysts typically examine the techniques an attacker uses, the tools involved, and the complexity of an operation to estimate the level of risk. New research from Anthropic, however, recommends that artificial intelligence is beginning to disrupt those assumptions.
The company's Frontier Red Team recently analyzed 832 user accounts that were removed from Anthropic's platforms for engaging in malicious cyber activity between March 2025 and March 2026. Researchers compared the observed behavior against the MITRE ATT&CK framework, a widely used industry resource that categorizes adversary tactics and techniques. Portions of the findings were also referenced in Verizon's 2026 Data Breach Investigations Report.
It's a signal to keep up with how cybercriminals are using AI. Rather than limiting AI to basic tasks, attackers are increasingly applying it to activities that take place after gaining access to a target environment. This trend suggests that AI is becoming part of deeper operational stages of cyber intrusions, including tasks that traditionally required stronger technical expertise.
Among all observed cases, malware development was the most common use of AI. Researchers found that 560 of the 832 analyzed accounts, representing more than two-thirds of the dataset, used AI-assisted tools to help create or modify malicious software. While this finding was expected, the more notable change appeared elsewhere.
Throughout the study period, researchers recorded a movement away from AI-assisted initial access activities and toward post-compromise operations. One example was account discovery, a process attackers use to identify valid user accounts within a breached network. AI-assisted account discovery increased by 8.9% during the reporting period. By contrast, AI-supported phishing activity declined by 8.6%.
The data also showed growing use of AI during lateral movement operations. Lateral movement refers to the actions attackers take after entering a network to expand their access and reach more valuable systems, users, or data repositories. According to the report, 54 of the 832 observed actors used AI assistance during this stage of an intrusion.
Historically, activities such as account discovery, privilege escalation, and lateral movement have been associated with more experienced operators because they require a stronger understanding of network environments and attack workflows. Researchers argue that AI is reducing those technical barriers, allowing a broader range of actors to perform tasks that were previously more difficult to execute effectively.
This change became visible in the study's risk assessment data. During the first half of the observation period, approximately 33% of threat actors were categorized as medium-risk or higher. During the second half, that proportion rose to 56%. Researchers described this increase as evidence that AI is helping a larger segment of the threat landscape carry out more advanced cyber activity.
The findings also raise questions about how the industry evaluates attacker sophistication. Security teams have long treated the number of techniques used during an attack as an indicator of capability. Anthropic's analysis suggests that this relationship is becoming less reliable in AI-assisted environments.
Researchers found only a small difference between lower-risk and higher-risk actors when measuring the number of techniques used. Less sophisticated actors employed an average of 16 techniques, while the most capable actors averaged 20. The narrow gap indicates that technique counts alone may no longer provide a meaningful way to prioritize threats.
The same pattern appeared when researchers examined how attackers interacted with AI systems. Whether actors used Claude Code, direct API access, or standard chat interfaces showed little connection to their assessed risk level. Simply identifying which AI tool was used did not provide a clear indication of the threat posed by an actor.
Instead, researchers found that the location of AI usage within the attack lifecycle was a stronger indicator of risk. Higher-risk operators tended to apply AI to technically demanding stages of an intrusion, including internal reconnaissance, privilege escalation, and lateral movement. These activities often have a direct impact on how effectively an attacker can establish control over a compromised environment.
Even that distinction may not remain useful indefinitely. Researchers observed that these more advanced use cases are gradually spreading throughout the broader threat ecosystem. As AI tools become more accessible and capable, activities once associated with a smaller group of highly skilled operators may become increasingly common.
Anthropic identified another characteristic that separated the most dangerous actors from the rest. Rather than using AI for isolated tasks, some operators built systems around AI models that connected multiple attack stages together. This allowed AI to support planning, execution, and decision-making across larger portions of an operation with limited human involvement.
Researchers describe this capability as agentic attack orchestration. In practical terms, it refers to AI systems that can assist with coordinating different phases of an intrusion, helping move an attack from one stage to another without requiring constant manual direction from an operator.
According to the report, this rising behavior exposes a limitation in existing cybersecurity frameworks. MITRE ATT&CK was designed to document attacker actions and techniques. It was not built to measure the degree of autonomy involved when AI systems help coordinate those actions.
Anthropic underlined this challenge using a cyber-espionage campaign it disrupted in November 2025. The operation involved attempts to use Claude Code in support of intrusion activity targeting organizations in multiple regions with relatively little direct human intervention.
When researchers mapped the operation to MITRE ATT&CK, it generated a profile containing 30 techniques across 13 tactics. On paper, that profile appeared comparable to many medium-risk actors included in the study. However, Anthropic's internal evaluation system assigned the operation the maximum possible risk score of 100.
Researchers argue that the discrepancy exists because current frameworks focus on what actions occur during an attack rather than how those actions are coordinated. An AI-assisted system capable of executing commands, identifying vulnerabilities, collecting credentials, and adapting to changing conditions throughout an intrusion presents a different operational challenge than a human manually performing each step.
The report notes that there are currently no ATT&CK categories specifically designed to capture autonomous orchestration, automated chaining of attack stages, or the reduction of human decision-making throughout an attack lifecycle.
Anthropic says it is actively discussing potential framework updates with MITRE to better account for AI-enabled attack behaviors. The company has also used insights from the research to strengthen safeguards within its own models, including controls intended to detect and prevent misuse involving malware development and large-scale data theft attempts.
For defenders, the findings suggest that traditional indicators may no longer provide a complete picture of cyber risk. A threat actor using AI to automate portions of an attack may achieve outcomes similar to those of a more experienced operator performing the same tasks manually. Likewise, an individual using a basic chat interface could potentially conduct operations that resemble those performed through more advanced integrations.