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Cyber threat intelligence in 2026 is converging on four connected concerns: identity abuse, faster exploitation of exposed software, AI-enabled operations, and risk that spreads through suppliers and connected services. The clearest evidence comes from reports published in 2026 about activity observed during 2025; it describes current patterns, not proof that every forecast has already come true. The numbers also come from different collections and should not be treated as a single global measure.
What the 2026 threat picture shows
Threat intelligence is most useful when it connects an attacker’s access, movement and impact across an organization—not when it treats phishing, cloud compromise, vulnerability exploitation or ransomware as isolated stories. Recent reporting points to attackers combining those paths: a stolen identity can open a cloud service, a vulnerable edge device can provide an entry point, and a compromised supplier can extend the consequences beyond one organization.
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The reports have different scopes. ENISA describes the European Union threat landscape; Google Cloud reports activity observed in its cloud environments; Mandiant analyzes targeted-attack investigations; and Microsoft highlights threats and defensive practices across its research and telemetry. Their findings add context to one another, but their percentages are not directly comparable.
| Report | What it covers | How to interpret it |
|---|---|---|
| ENISA, 2026 Threat Landscape | Events observed from January through December 2025 in the EU threat landscape. | Useful for understanding regional incident patterns and affected sectors; it is not a census of all global cyber activity. |
| Google Cloud, H1 2026 report | A subset of activity observed in Google Cloud environments during H2 2025, with a comparison to H1 2025 for some measures. | Cloud-provider observations reveal patterns in that environment, not universal rates for all organizations. |
| Mandiant, M-Trends 2026 | Investigations of targeted attacks during 2025. | Investigation findings describe cases Mandiant handled, not the distribution of every incident worldwide. |
| Microsoft threat reporting | Emerging threats and defensive recommendations informed by Microsoft research and telemetry. | Use its recommendations as guidance, while keeping in mind the visibility and scope of the reporting source. |
Why identity and trust are central
Attackers increasingly exploit trust in people, accounts and connected services rather than relying only on a technical flaw. Google Cloud’s H1 2026 report says identity compromise underpinned 83% of compromises observed in its cloud findings for H2 2025. The report also describes voice phishing and theft of third-party SaaS tokens. That 83% is specific to Google Cloud’s observed cases, not an estimate for all cloud or enterprise compromises.
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Mandiant’s M-Trends 2026 report, based on its 2025 targeted-attack investigations, found exploits were the most common initial infection vector at 32%. Voice phishing accounted for 11% and email phishing for 6% of observed initial infection vectors in that dataset. These figures have a different scope from Google Cloud’s findings and should not be combined into an overall prevalence rate. Mandiant notes that interactive voice attacks can evade automated technical controls, so detecting them requires attention to identity-verification processes and unusual account activity, not just email security.
Identity risk also includes non-human accounts, cloud permissions and tokens that let services connect to one another. An attacker who steals or misuses a valid credential may look like a legitimate user unless defenders correlate sign-in, device, application and cloud-control-plane activity. In ransomware cases in Mandiant’s 2025 investigations, prior compromise was the most common initial vector at 30%; access was sometimes handed off between threat clusters. That pattern makes it important to investigate how access was obtained and transferred, not only the final ransomware deployment.
Why vulnerability exploitation is moving faster
The time available to patch exposed systems is shrinking. Google Cloud reported that the interval between vulnerability disclosure and active exploitation fell from weeks to days in its H2 2025 observations. In that same set of observed cloud initial-access vectors, exploitation of third-party software accounted for 44.5%, compared with 2.9% in H1 2025; weak or absent credentials accounted for 27.2% in H2. These are source-specific findings, and the comparison is between Google Cloud’s reported periods, not a universal measure of risk.
ENISA’s 2026 landscape gives a separate view. Among unauthorized-access incidents for which ENISA could identify an intrusion vector—a subset representing 5% of those incidents—60% leveraged a vulnerability. The limited subset matters: the figure applies to cases with an identifiable vector, not to all unauthorized-access incidents. Mandiant also identifies exploits as the leading initial infection vector in its 2025 targeted-attack investigations and calls out zero-day vulnerabilities affecting edge devices.
The practical implication is that asset and dependency visibility must include systems outside the obvious workstation fleet: internet-facing appliances, edge devices, third-party software and services, and components embedded in business applications. A vulnerability inventory is only useful if it can be matched to actual exposure and prioritized for remediation.
How AI is changing cyber threats—and what it is not changing
AI is an enabler and an attack surface, but current reporting does not support the claim that AI has replaced familiar causes of compromise. Mandiant observed adversaries using AI to increase productivity in reconnaissance, social engineering and malware development. Reported examples included AI-themed lures, credential theft targeting AI applications, and malware querying large language models in attempts to evade detection. Mandiant cautions that breaches in 2025 were not directly caused by AI; fundamental human and systemic weaknesses remained the principal failure modes.
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ENISA describes AI-generated text, synthetic audio and synthetic video being used in information manipulation, with AI extending the reach of malicious content. It also notes that AI environments themselves expand the attack surface. Microsoft describes attackers targeting AI systems to execute commands, steal serving capacity or exfiltrate data. These are distinct concerns: AI can help an attacker conduct an operation, be used to manipulate people, or become an asset that attackers target.
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How suppliers and connected services amplify impact
A supplier or shared service can become an indirect route into multiple organizations. ENISA warns that third-party and supply-chain attacks can cause large-scale or high-impact incidents. Microsoft also highlights open-source supply-chain compromise and edge-device attacks among significant emerging threats. The security question is therefore not only whether an organization’s own systems are patched, but also which external software, providers and connected services can affect its operations or data.
ENISA’s 2026 reporting found that 73% of targeted organizations were essential or important entities under NIS2, while public administration accounted for 32% of targeted cases. Those percentages describe ENISA’s reported EU landscape; they do not establish the same distribution elsewhere. They underscore why supplier exposure and service dependencies matter especially to organizations whose disruption can affect public or essential services.
Map critical suppliers and technical dependencies to the systems and business functions that rely on them. For high-impact services, include supplier incidents in response planning: identify who can confirm a compromise, what data or access may be exposed, how to isolate a dependency, and how to preserve evidence across organizational boundaries.
Why ransomware and geopolitical activity still matter
ENISA identifies ransomware as the most short-term impactful incident type in its EU threat landscape, including extortion through encryption and data theft. It also observes hacktivist distributed denial-of-service activity against essential entities amid geopolitical developments. These activities can disrupt services even when the actor’s goal differs from financial extortion.
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ENISA notes that threat categories can blur: similar techniques, infrastructure and access mechanisms appear across reporting on cybercrime, hacktivism and state-linked activity, despite different objectives. For defenders, attribution labels should not substitute for operational analysis. The immediate questions are what access the actor has, what systems are exposed, what activity is occurring, and what impact is plausible.
Mandiant reported a global median dwell time of 14 days in its 2026 report on 2025 investigations, up from 11 days in 2024. This is a measure from Mandiant’s investigated cases, not a universal average. It is a reminder to build detection and investigation processes that can find an intrusion before the attacker’s final action becomes visible.
How to turn threat intelligence into defensive priorities
Threat intelligence should change what an organization monitors, fixes and rehearses. Microsoft recommends correlating endpoint, identity, cloud, application, email and network signals. ENISA and vendor reporting support prioritizing identity controls, exposure reduction, supplier dependencies and readiness to investigate cloud environments.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minute- Correlate signals across control planes. Connect endpoint, identity, cloud, application, email and network telemetry so an unusual sign-in can be evaluated alongside device behavior, token use and cloud configuration changes. Maintain enough logging to reconstruct activity in cloud environments.
- Strengthen identity verification and privilege. Prioritize phishing-resistant multifactor authentication, passkeys where supported, least privilege and disciplined identity hygiene. Review both human and non-human accounts, privileged access, stale identities and SaaS tokens.
- Reduce exposure in software and edge assets. Keep an inventory of internet-facing systems, third-party software and edge devices. Use exposure and vulnerability intelligence to prioritize reachable, high-impact weaknesses, and establish a process to act quickly when exploitation begins.
- Map dependencies and plan for supplier incidents. Identify critical providers, software components and services, then document their access, business impact and response contacts. Include scenarios in which a supplier or shared service is compromised.
- Extend monitoring to AI environments. Know which AI applications, data stores and model-serving systems the organization uses. Monitor access and privilege around them, and investigate suspicious attempts to execute commands, misuse serving capacity or extract data.
- Test detection and response, not just prevention. Rehearse voice-phishing reports, token compromise, exposed edge devices, supplier incidents and ransomware extortion. Define how teams preserve evidence, revoke access, contain systems and coordinate with affected providers.
These controls reduce exposure and improve detection; none guarantees prevention. CTI is most valuable when it helps an organization match external developments to its own identities, software, suppliers and critical services, then make a specific operational change.
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