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Cyber threat intelligence in 2026 is being shaped by four connected risks: identity abuse, faster exploitation of exposed software, AI-assisted activity, and attacks that spread through suppliers and connected services. The clearest evidence comes from activity observed in 2025 and described in reports published in 2026; it should be read as a current assessment, not proof that every forecast has already happened.
What do the 2026 reports actually show?
The figures below describe different populations and collection methods. ENISA assesses the EU threat landscape; Google Cloud reports activity visible in its cloud environments; Mandiant analyzes targeted-attack investigations; Microsoft highlights emerging threats and defensive priorities. Their percentages are not interchangeable and do not add up to a universal estimate of cyber risk.
| Source and scope | Finding | How to interpret it |
|---|---|---|
| ENISA, 2026 Threat Landscape, covering events from January through December 2025 | Vulnerabilities were used in 60% of identified intrusion vectors within a subset of unauthorized-access incidents for which ENISA could identify a vector. That subset represented 5% of unauthorized-access incidents. | This is a finding about a limited, classifiable subset, not all unauthorized access. |
| ENISA, 2026 Threat Landscape | Of targeted organizations, 73% were essential or important entities under NIS2; public administration accounted for 32% of targeted cases. | These figures describe the entities and cases in ENISA’s EU reporting, not worldwide targeting. |
| Mandiant, M-Trends 2026, based on 2025 investigations | Median global dwell time was 14 days, compared with 11 days in 2024. Exploits were 32% of observed initial infection vectors, voice phishing 11%, and email phishing 6%. | These are investigation-based findings, not a census of all incidents. |
| Mandiant, M-Trends 2026 ransomware cases | Prior compromise was the most common initial vector, at 30%. | In some cases, access was handed off between threat clusters. |
| Google Cloud, H1 2026 report on H2 2025 cloud observations | Identity compromise underpinned 83% of observed compromises. Third-party software exploitation accounted for 44.5% of observed initial access vectors, compared with 2.9% in H1 2025; weak or absent credentials accounted for 27.2% in H2 2025. | These rates reflect a subset of activity observed in Google Cloud environments, not all cloud or global incidents. |
Why are identity and trust central CTI concerns?
Attackers increasingly target the credentials, permissions, and trusted relationships that let them act as legitimate users. That makes identity telemetry essential to threat analysis: an unusual sign-in, a newly granted privilege, a stolen SaaS token, and suspicious activity in a cloud control plane may be parts of one intrusion rather than isolated alerts.
Voice phishing can bypass familiar assumptions
Mandiant notes that interactive voice attacks are more resilient to automated technical controls and require different detection strategies. A caller can pressure a person to disclose credentials, approve access, or change an account setting. A useful CTI program therefore connects reports of impersonation and social engineering to identity-provider logs, help-desk procedures, and subsequent account activity.
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Trust relationships create paths beyond the first account
Google Cloud’s observations include vishing and theft of third-party SaaS tokens. A token or trusted integration can provide access without the attacker repeating a conventional password login. Monitor both human and non-human identities, review application permissions and token use, and investigate activity across connected services rather than stopping at the first compromised account.
Why is vulnerability exploitation moving faster?
Google Cloud reports that the interval between vulnerability disclosure and active exploitation contracted from weeks to days in its H2 2025 observations. Mandiant also identifies exploits as the leading initial infection vector in its 2025 targeted-attack investigations, including zero-day vulnerabilities affecting edge devices. For defenders, the implication is operational: exposure management and remediation decisions need to account for internet reachability, asset importance, and evidence of exploitation—not just a vulnerability’s publication date.
Exposed software and edge devices deserve priority
Third-party software can be a route into an organization even when its own systems are well managed. Edge devices are especially consequential because they sit at network boundaries and may have direct exposure to the internet. Keep an accurate inventory of externally reachable software and devices, identify who owns each asset, and track vendor security advisories alongside threat intelligence on active exploitation.
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Supply-chain incidents can expand the blast radius
ENISA warns that attacks on suppliers and other third parties can cause large-scale or high-impact incidents. Microsoft also highlights open-source supply-chain compromise and edge-device attacks among emerging threats. CTI should map dependencies—including software, service providers, and integrations—to the business services that rely on them. A supplier alert matters most when it can be tied to a specific dependency, exposed asset, or access path in your environment.
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How is AI changing cyber threats in 2026?
AI is an enabler and an attack surface, but the evidence does not support treating it as the primary cause of most successful intrusions. Mandiant observed AI being used to support reconnaissance, social engineering, and malware development, while emphasizing that fundamental human and systemic weaknesses remained the principal failure modes in 2025.
AI can assist existing attack techniques
Mandiant describes AI-themed lures, credential theft aimed at AI applications, and malware querying large language models in attempts to evade detection. ENISA also discusses AI-generated text, synthetic audio, and synthetic video in information manipulation. These uses can make familiar tactics more scalable or persuasive, but CTI teams should distinguish observed techniques from speculation about autonomous attacks.
AI systems themselves need protection
ENISA notes that AI environments extend the attack surface. Microsoft describes attackers targeting AI systems to execute commands, steal serving capacity, or exfiltrate data. Include AI services, their identities and permissions, connected data sources, and administrative interfaces in asset and threat models. Treat access to an AI application as a security question, not simply a productivity-tool decision.
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ENISA identifies ransomware as the most short-term impactful incident type in its EU landscape. Extortion can involve encryption, data theft, or both, and prior compromise may be followed by access being transferred between threat clusters. Investigations should therefore preserve evidence about how access was obtained and whether other actors or services were involved.
ENISA also reports hacktivist distributed-denial-of-service activity against essential entities amid geopolitical developments. It observes that threat categories can blur: cybercrime, hacktivist, and state-linked reporting may feature similar techniques, infrastructure, or access mechanisms even when the groups’ objectives differ. Classifying an incident by a single label too early can obscure shared infrastructure or a changing operational context.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How should security teams turn CTI into action?
Threat intelligence is most useful when it changes what an organization can see, prioritize, or do. Microsoft recommends correlating endpoint, identity, cloud, application, email, and network signals. That cross-domain view can reveal the sequence linking a phished account, a suspicious SaaS token, an exposed application, and later movement through cloud services.
- Connect telemetry. Make identity, endpoint, cloud, application, email, and network events searchable together. Record enough context to relate an alert to an account, device, service, and business owner.
- Review identity exposure. Monitor human and service identities, privilege changes, SaaS tokens, and cloud control-plane activity. Prioritize phishing-resistant MFA, passkeys, disciplined identity hygiene, and least privilege.
- Reduce exploitable exposure. Inventory third-party software and edge assets, identify internet-facing systems, and use active-exploitation information to prioritize remediation. Confirm that fixes are deployed rather than relying only on advisory publication or ticket closure.
- Map suppliers and connected services. Document critical dependencies and the access they receive. When a supplier or component is implicated, assess which systems, credentials, integrations, and business services could be affected.
- Prepare for cloud investigation. Establish forensic readiness: retain relevant logs, know how to retrieve them, and define who can preserve evidence from cloud services during an incident.
- Include AI and data environments. Track AI services, their access paths, connected data, and administrative controls. Investigate unusual use of AI resources as part of the broader identity and application picture.
These controls reduce exposure and improve detection; they do not guarantee prevention. The practical measure of a CTI program is whether it helps teams connect relevant signals and act before an incident spreads.
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How to read threat forecasts without overstating them
ENISA’s 2026 landscape analyzes 2025 events and describes the EU environment. Vendor reports offer deeper views into their own telemetry, customers, or investigations, but those views cannot be assumed to represent the whole internet. Keep the reporting period, geography, collection method, denominator, and whether a statement is observed or forecast attached to every statistic or claim.
ENISA Executive Director Juhan Lepassaar described the threat landscape as showing “how threats become more interconnected and how threat groups spread their impact across the larger map of digital services and infrastructures.” That is a useful framing for CTI in 2026: track the relationships between identity, exposed technology, suppliers, and services—not only a list of threat actors or indicators.
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