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In 2026, AI is changing cybersecurity on both sides: attackers are using it to scale phishing, impersonation and some live intrusions, while AI applications and agents create new ways to expose data or trigger unauthorized actions. That does not mean every attack is autonomous or AI-generated. Stolen credentials, weak account recovery and familiar social-engineering tactics remain central to the threat.
How are hackers using AI in 2026?
Reports describe AI being used to accelerate or support parts of attacks, including phishing, voice-agent scams, synthetic-media impersonation and attempts to manipulate AI systems. Check Point Research’s July 14, 2026, AI Security Report describes AI moving from a development aid to an operator in some intrusions. Its phrase, “AI has crossed from assistant to operator,” characterizes those reported cases; it does not establish that attacks are generally autonomous.
AI can make an attack more convincing or easier to scale, but it does not replace the underlying opportunity. A convincing message still needs a target to trust it, an account or process to exploit, or a weakness in how access and payments are approved. Gartner analyst Craig Porter put the distinction plainly: “Most attacks will continue to rely on users, stolen credentials, weak recovery processes, and familiar technical methods.”
Gartner’s September 2026 survey also shows why familiar channels still matter: 79% of the surveyed senior cybersecurity leaders reported at least one email phishing, spear-phishing or business email compromise incident in their organization in the previous 12 months. Separately, 58% reported at least one vishing or smishing incident. These are survey results from 297 senior cybersecurity leaders, not rates for all businesses or individuals.
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Can you trust a video or voice call anymore?
A voice or video call can no longer serve as sufficient proof of identity when the request involves money, credentials, sensitive data or privileged access. Gartner found that 41% of surveyed CISOs reported at least one deepfake-related social-engineering incident during an employee audio call in the previous 12 months; 36% reported one during a video call. Gartner surveyed 297 senior cybersecurity leaders from March through May 2026 and published the results on September 22, 2026. The percentages describe those respondents’ organizations, not the share of all organizations affected.
Impersonation may combine synthetic voice or video with stolen or aggregated personal context, email, documents and other channels. A familiar face, voice or meeting invite should therefore be treated as a communication signal, not as the final authorization step. Gartner analyst Craig Porter warned that attackers can combine “phishing, business email compromise, synthetic media, and aggregated personal context across multiple channels.”
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Verify the request, not just the person’s appearance
- For a consequential request, confirm it through a separate, already trusted channel, such as a known phone number or an established approval workflow. Do not use contact details supplied in the suspicious message or call.
- Require a second authorized person or an independent approval step for high-impact actions such as payment changes, urgent transfers, access grants or disclosure of sensitive information.
- Give employees a clear way to pause and report unusual requests without being penalized for delaying a transaction.
- Correlate a suspicious communication with account events, including password resets, new devices, privilege changes and transaction activity. A plausible call may coincide with a compromised account or a manipulated recovery process.
Deepfake detection tools may add a signal, but they should not make the decision on their own. Gartner’s guidance is explicit: “There is no one cybersecurity control that will protect you.”
What is prompt injection, and can it expose your data?
Prompt injection is an attempt to influence an AI system through instructions embedded in content it reads or receives. For example, text in a document or web page may try to persuade an AI assistant to ignore its intended rules, reveal information or take an action. The risk is not limited to a chatbot’s answer: an AI application connected to files, accounts, business systems or external tools may have access to data or actions that a user could not safely expose to untrusted content.
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Gartner identifies prompt injection and AI application compromise among critical threats. Check Point Research also describes indirect prompt injection and the risk of agents trusting planted configuration or other content that influences their behavior. A successful manipulation can lead to data exposure, unauthorized actions or safeguards being bypassed; the result depends on the AI system’s access, design and controls.
Reduce the impact of a manipulated AI system
- Inventory AI tools, agents, plugins and integrations, including employee-used applications that may not have been formally approved.
- Threat-model what each system can read, change, send or execute. Give it only the data access and permissions required for its task.
- Require human confirmation before consequential actions such as sending sensitive data, changing permissions, making purchases or executing code.
- Test systems with untrusted documents, web pages and messages to see whether embedded instructions can alter behavior or expose information.
- Monitor runtime behavior and review software components and build pipelines, particularly where an AI application depends on third-party services or code.
Are AI agents becoming a cybersecurity risk?
They can be, especially when an agent can act on information from untrusted sources while holding access to business data, accounts or tools. An agent can extend the consequences of a prompt-injection flaw: instead of merely producing a misleading response, it may be able to retrieve a file, send a message or change a system. This is a risk to assess, not proof that every agent is compromised or unsafe.
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Google Cloud’s 2026 forecast calls attention to shadow-agent risk alongside identity and access management, ransomware and data theft, virtualization infrastructure and nation-state activity. The practical concern is not the label “agent” by itself, but the combination of autonomy, broad permissions, weak oversight and exposure to untrusted input.
- Keep an inventory of agents and their owners, connected services, data access and permitted actions.
- Use narrow, revocable credentials rather than shared or broadly privileged accounts.
- Separate reading information from approving or executing high-impact actions.
- Log agent activity and alert on unusual access, privilege changes, data transfers or behavior outside its intended task.
Why do web-based attacks still matter?
AI-related attacks are only part of the picture. Check Point’s 2026 Cyber Security Report describes exposure caused by misconfiguration, identity weaknesses and unmanaged assets across cloud, edge, SaaS and on-premises environments. These paths can connect: an exposed service, weak account recovery or stolen credential may provide access that attackers then use to reach other systems. The report does not establish that all web attacks are AI-generated.
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Google Cloud’s outlook also flags MFA-bypass tactics, extortion, virtualization infrastructure and nation-state activity as concerns for 2026. Trend Micro’s predictions include identity and session hijacking, automated ransomware and AI-accelerated exploitation. These are vendor forecasts, not counts of incidents that have already occurred. They are useful as planning scenarios, but should not be read as evidence that every organization will face each threat.
Prioritize the paths attackers can reuse
- Find and remediate exposed or misconfigured internet-facing assets, and remove systems no longer in use.
- Review identity permissions, privileged accounts and recovery processes. Monitor what happens after login or password reset, not only whether authentication succeeded.
- Use phishing-resistant authentication for high-value workflows where compatible, and make recovery at least as carefully controlled as initial enrollment.
- Maintain an inventory of software components and strengthen build-pipeline controls so weaknesses in dependencies or delivery processes are easier to identify and contain.
A FIDO2 security key is one possible hardware implementation of phishing-resistant authentication. It does not detect deepfakes or prevent every social-engineering attack, and compatibility, enrollment and account-recovery requirements vary by service and organization.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the 2026 figures do—and do not—show
The available figures come from different methods and populations. Survey responses measure what participants reported or believed; vendor telemetry describes the observations and scope of a particular provider; forecasts describe expectations. They should not be combined into a single prevalence rate.
| Source and evidence type | Finding | How to interpret it |
|---|---|---|
| Gartner, survey of 297 senior cybersecurity leaders, March–May 2026; published September 22, 2026 | 41% reported at least one deepfake-related social-engineering incident on an employee audio call; 36% reported one on video, each during the prior 12 months. | Reports from surveyed CISOs’ organizations; not the share of all businesses or people affected. |
| Gartner, same survey | 79% reported at least one email phishing, spear-phishing or business email compromise incident, and 58% reported at least one vishing or smishing incident, during the prior 12 months. | Separate organizational survey results that show conventional channels remain relevant. |
| World Economic Forum, 2026 outlook survey | 94% of respondents viewed AI as the most significant driver of cybersecurity change in the year ahead; 64% said their organizations assessed AI-tool security in 2026, up from 37% in 2025; 87% identified AI-related vulnerabilities as the fastest-growing cyber risk over the course of 2025. | These are respondents’ assessments and reported organizational practices, not incident rates or objective measurements of attack volume. |
| Check Point Research, 2026 AI Security Report | High-risk prompts doubled from 2% to 4% during the prior year; organizations used an average of 10 AI applications each month. Business Services had a 5.91% rate of high-risk GenAI prompts. | Check Point’s telemetry and reporting context, not universal business counts. The sector figure was described as nearly one in every 17 AI interactions in Business Services. |
How should organizations plan for the rest of 2026?
Use incident reporting to understand what has been observed and forecasts to test whether existing controls would hold up under plausible scenarios. Check Point Research’s July report describes reported AI use in live intrusions and attack tooling. Gartner’s survey measures incidents reported by its respondents. Google Cloud and Trend Micro offer vendor predictions for the year ahead, while the World Economic Forum’s outlook reflects survey-based assessments of cyber risk and readiness. None of those forecast categories should be mistaken for a confirmed incident count.
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A useful plan joins communication security, identity controls and AI governance instead of treating each as a separate problem:
Quick Recap
- Set verification rules. Define which requests require independent confirmation or dual approval, including requests made by email, voice, video, collaboration tools or AI applications.
- Harden identity and recovery. Apply phishing-resistant authentication where appropriate, restrict privileged access, protect account recovery and watch for suspicious activity after a reset or new-device sign-in.
- Constrain AI access. Track applications and integrations, limit the data and actions available to each system, and test for prompt injection using realistic untrusted inputs.
- Update response playbooks. Include multimodal impersonation and misused agents; connect communication reports to identity, device, privilege and transaction signals.
- Review exposure continuously. Check internet-facing assets, cloud and SaaS configurations, software components and build pipelines for weaknesses that could join into a broader attack path.
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