Understanding Google’s Cybersecurity Forecast 2026

Every year, Google’s security teams publish a forward-looking assessment of the threats they expect in the months ahead. The Cybersecurity Forecast 2026 is Google Cloud’s annual threat intelligence report, built on frontline data from the Google Threat Intelligence Group, Mandiant, and Google Security Operations, so it reflects what those teams are already seeing in live attacks rather than speculation about what might come next.

Published: May 2026. Updated: August 2026. Reviewed by Encryption Consulting’s PKI Advisory team.

This post walks through that report for the people who actually have to act on it. It follows the same three themes Google uses: AI, cybercrime, and nation states, and keeps returning to one idea that runs through the whole document. In 2026, the thing you are really defending is identity, and identity now includes software, not just people.

One line from the report deserves its own headline: your AI agents need their own identities. That is where this walkthrough begins.

Why Does This Forecast Matter for Security and PKI Teams?

It matters because the report is not a marketing document. It is built from what Mandiant’s incident responders and Google’s own threat hunters saw in live cases through 2025, so each prediction maps to a control gap a security team can actually close this year. Google’s own Cloud Threat Horizons research, cited alongside the forecast, found that more than 70 percent of cloud breaches now trace back to a compromised identity rather than a software exploit. That single number explains why identity, not malware signatures, is the organizing theme of the entire 2026 forecast, and why PKI, certificate, and key management teams have a direct stake in a report that on its surface reads like a threat intelligence briefing.

For a CISO, the forecast is a budget argument. For a PKI or platform engineer, it is a to-do list: which credentials are long-lived and should not be, which service accounts are shared and should not be, and which workloads still authenticate with a static secret instead of a short-lived certificate.

How Should You Prioritize Among the Forecasted Threats?

Not every prediction in the report deserves the same amount of your team’s time this quarter. A useful way to triage is to rank each theme by how directly it depends on identity and cryptographic controls you can actually change, versus threats that mostly require detection and process work.

1. Non-human and AI agent identity ranks highest for most enterprises, because it is a new attack surface growing faster than governance around it, and the fix (short-lived, workload-scoped credentials) is a cryptographic project your team already knows how to run.
2. Credential-based initial access (phishing, vishing, MFA bypass) ranks next, since it is the single largest entry point across ransomware, cybercrime, and nation-state campaigns alike, and phishing-resistant authentication closes it directly.
3. Infrastructure-layer attacks (hypervisors, edge devices, managed file transfer software) rank third, because they require patching and monitoring investment more than cryptographic redesign, though certificate-based device authentication helps.
4. Long-horizon cryptographic risk (post-quantum migration, cryptographic agility) ranks fourth on urgency but first on lead time, since a multi-year migration has to start well before the threat becomes acute.

The rest of this post follows the report’s own three themes, then returns to this prioritization with a concrete decision table.

What AI-Driven Threats Does the Report Highlight?

Google’s lead prediction is straightforward: in 2026, AI becomes a routine part of how attackers operate rather than the exception. Adversaries are using AI to work faster and at a larger scale across the whole attack lifecycle, including research, social engineering, malware, and increasingly, automation through AI agents. None of this requires a breakthrough. It simply lowers the cost and skill needed to run a good attack, which means more attacks from more people.

Prompt Injection

If there is one new AI threat to understand this year, make it prompt injection. The report flags it as a present danger, not a future one.

Here is the core problem in simple terms. A large language model reads its instructions and the data it is working on through the same channel. It cannot reliably tell the difference between “this is a command from my owner” and “this is text I am supposed to summarize.” So if an attacker hides an instruction inside data the model later reads, the model may quietly follow it. That is prompt injection, and it sits at the top of OWASP’s 2025 Top 10 for LLM Applications as LLM01.

Prompt injection comes in two forms. Direct injection is when a user types something like “ignore your previous instructions” straight into a chatbot. Indirect injection is sneakier: the malicious instruction lives inside a web page, a PDF, an email, or even the pixels of an image, and the model runs into it while doing a normal task. Picture an AI assistant that summarizes your inbox using a privileged account. A single malicious email could tell it to forward sensitive messages somewhere else, and it might just do it.

You cannot fully patch this away, because it abuses how the model works rather than a single bug.

The realistic defense is layered. Google describes model hardening plus system-level guardrails, including classifiers that filter malicious instructions out of untrusted data, and user confirmation for high-risk actions. OWASP adds the controls that matter most to engineers: separate and clearly label untrusted content, validate and sanitize model output, keep a human in the loop for sensitive operations, and tightly limit what the model is allowed to do. That last point connects to another OWASP risk, Excessive Agency (LLM06), and it leads straight into the most important architecture shift of the year.

Why Your AI Agents Need Their Own Identities

An AI agent is software that does not just answer questions, it takes actions. It reads files, calls APIs, queries databases, and chains steps together to finish a task on its own. That is genuinely useful, and it is spreading fast. Gartner predicts that 40 percent of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5 percent in 2025.

Here is a question every security engineer should ask: when an agent calls your payroll system at 2 a.m., who exactly is making that request? In most organizations today, the honest answer is often a shared service account with a long-lived API key and broad standing access. That is the gap. Google calls the fix the AI Agent Paradigm Shift, and its central principle is treating each AI agent as a distinct digital actor with its own managed identity.

This is not a brand-new idea bolted onto AI. It is zero trust applied to non-human identities, and it sits alongside the wider non-human identity explosion already reshaping enterprise IAM. NIST SP 800-207, the foundational zero trust document, already defines a “subject” to include applications and other non-human entities that request resources, and it insists that every request be authenticated and authorized on its own, with access granted per session under least privilege. An AI agent is exactly that kind of subject. The forecast describes the practical version of this as “agentic identity management,” built on a few clear principles:

• Least privilege by default. An agent gets only the narrow access its current task needs, nothing more.
• Just-in-time access. Permissions are temporary and task-specific, granted at the moment of use and then revoked, instead of standing access that never expires.
• A clear chain of delegation. You can always answer “this agent is acting on behalf of this user for this purpose,” and prove it.
• Continuous, context-aware evaluation. Trust is recalculated as conditions change, not granted once and forgotten.

Underneath these principles is infrastructure that PKI and platform engineers will recognize. Instead of static secrets, agents and workloads get short-lived, cryptographically verifiable identities: short-lived X.509 or JWT credentials, workload certificates, and mutual TLS between services so each side proves who it is on every call. Workload identity frameworks such as SPIFFE and SPIRE issue a verifiable identity document to each workload, and certificates rotate automatically so a leaked credential is only useful for minutes, not months. Cloud-native teams pair this with Workload Identity Federation and Cloud Infrastructure Entitlement Management (CIEM) tooling, which the report calls out as the emerging standard for governing which non-human identity can reach which resource.

Speed is why this matters. An agent can take hundreds of actions before a human notices anything, so the wide, permanent permissions that were once considered acceptable with monitoring are no longer safe. Granular, short-lived, verifiable identity is the control that keeps pace.

When the Caller Sounds Exactly Like Your CFO

Google’s report names ShinyHunters (tracked as UNC6240) as one of the sophisticated threat actors expected to accelerate highly manipulative, AI-enabled social engineering in 2026, calling it one of the most damaging trends of the year. Their success rarely depends on a technical exploit. In 2025, their weapon of choice was voice phishing, or vishing, and the report expects it to be supercharged with AI voice cloning that can convincingly imitate an executive or an IT staff member.

AI also makes the rest of the con cheaper: automated research on targets, polished phishing messages with no telltale typos, and personalized lures at scale. Because the attack targets human trust rather than your firewall, your firewall never sees it coming. The defense here is process, not just technology. Build verification steps that do not rely on recognizing a voice, such as callback procedures on known numbers and out-of-band approval for sensitive requests like password resets, payments, or MFA changes. A confident voice on the phone should never be enough on its own to move money or reset access.

Shadow Agents: The Part Nobody Approved

Shadow IT used to mean employees quietly installing an unsanctioned app. By 2026, the proliferation of capable, autonomous AI agents escalates that into a sharper problem: shadow agents. Employees deploy these agents on their own to get work done, with or without approval, and those agents quietly connect to email, SaaS tools, and file stores. The result is invisible, uncontrolled data pipelines that can lead to data leaks, compliance violations, and intellectual property theft.

Banning agents outright is not realistic. It only pushes usage off the corporate network and removes what little visibility security teams had. The better path is treating AI security and governance as its own discipline, built on a secure-by-design approach from the start. That means deploying controls to discover and inventory every agent, safely route and monitor all agent traffic, apply the same identity and access rules given to a human or a vendor, and keep a full audit trail of which agent touched which data under which policy. The organizations that come out ahead will be the ones that enable AI innovation while keeping the whole environment auditable.

The Upside: A More Capable SOC

None of this is one-sided. Defenders get to use the same technology. The report describes an agentic security operations center where analysts stop drowning in raw alerts and start directing AI agents instead. An alert can arrive already enriched with a case summary, a decoded malicious script, and a mapping to known attacker techniques, so a responder validates and approves a containment action in minutes instead of hours. The goal is to scale human judgment, not replace it. The analyst still owns the final call.

What Cybercrime Trends Does the Report Project for 2026?

AI may be the new tool, but cybercrime is still the main event. Google names financially motivated crime the most disruptive global threat for 2026, and most of it traces back to the same theme: attackers abusing trust and identity to get in, then hitting the place where one breach does the most damage.

Ransomware and Extortion Stay on Top

The combination of ransomware, data theft, and multi-layered extortion remains the costliest category of cybercrime, and the damage spreads far beyond the first victim into suppliers, customers, and whole communities. Volume is rising too. Google reports that 2,302 victims appeared on data leak sites in the first quarter of 2025, the highest single-quarter count since it began tracking in 2020.

Two tactics stand out for engineers. First, attackers keep using vishing and other social engineering to get around multi-factor authentication (MFA), a reminder that MFA is necessary but not magic, especially the kinds that can be phished. Phishing-resistant methods bound to a device and a verified identity hold up far better than one-time codes. Second, criminals target managed file transfer (MFT) software, the systems companies use to move files between partners, because compromising one of them can let an attacker steal data from hundreds of organizations at once. That is supply chain leverage, and it rewards knowing exactly which third parties can reach your data.

Crime Moves On Chain

As finance adopts cryptocurrencies, stablecoins, and tokenized assets, attackers follow the money onto public blockchains. The report expects continued high-value attacks on decentralized finance platforms and exchanges, plus supply chain attacks paired with digital asset theft. Longer term, criminals may move parts of their own operations on chain, using the blockchain itself for command and control and data exfiltration, which makes their infrastructure very hard to take down.

That permanence cuts both ways, though. The same ledger that protects attacker infrastructure also records every move they make. Every funded wallet and deployed contract leaves a permanent, public record, which is a gift for attribution and lets investigators link campaigns years apart. For defenders holding crypto assets, the practical lesson is an old one: the private keys that control those assets matter more than almost anything else. Generate and store them in hardware that never exposes the raw key, enforce strong approval workflows for transactions, and treat key management as a first-class security program rather than an afterthought.

The Hypervisor Becomes the Prize

This is one of the most important technical warnings in the report, and it is easy to miss. As defenders hardened the systems inside virtual machines, attackers moved down a layer, to the virtualization fabric that hosts them.

That layer is now a critical blind spot. Hypervisors often run without endpoint detection and response (EDR). They get patched late. They ship with insecure default settings. Most teams watch the user endpoints and guest systems, not the underlying virtualization layer, yet that layer hosts every enterprise application and ties into core identity services. A single compromise can hand an attacker control of the entire digital estate. In practice, that means bypassing the security tools inside the guests and mass-encrypting the virtual disks underneath.

Ransomware usually crawls across a network for days. A hypervisor attack can take down hundreds of systems in hours. The fixes are concrete: monitor the fabric itself, not just the guests, harden the default settings, and keep the management plane patched and segmented.

Factories and Pipelines: ICS and OT

For industrial control systems and operational technology, the main 2026 threat is also cybercrime, with a clever twist. Attackers do not always need to reach the factory floor itself. By hitting core business software such as enterprise resource planning (ERP) systems, they can cut off the data that production depends on. That halts operations and pressures victims into paying quickly, all without touching a single machine. Meanwhile, basic hygiene problems like insecure remote access keep letting ordinary Windows malware reach operational networks.

Google’s guidance maps cleanly to well-known controls. Segment the network so ransomware cannot pivot from the IT side into operations. Protect all remote access with multi-factor authentication and least privilege so stolen credentials do not open the door. And keep immutable, offline backups of both industrial configurations and critical business data, because recovery is what turns a disaster into an inconvenience.

What Nation-State Activity Does the Report Anticipate?

The third theme is government-backed activity. Four actors dominate, each with its own goals, but notice the common thread underneath them: stolen credentials, abused trust in third parties, and patient access. It is the identity story again, played at a geopolitical level.

Russia is expected to widen its focus from short-term wartime support in Ukraine toward longer-term strategic goals, including quietly building footholds in critical infrastructure abroad. Pro-Russian influence operations and hacktivist groups stay active against the West, with elections a recurring target. Operational technology is at real risk too. Norwegian intelligence attributed an April 2025 compromise of a Norwegian dam to pro-Russian actors.

China is projected to run the highest volume of operations of any nation, with a growing emphasis on stealth. Its actors favor edge devices like routers and VPN appliances that usually lack endpoint detection, lean on zero-day vulnerabilities, and target third-party providers so that one trusted partner becomes a path into many downstream victims. The semiconductor sector is a particular focus, driven by competition and AI-related demand.

Iran, according to the report, is expected to keep combining espionage, disruptive operations, hacktivism, and financially motivated activity, an overlap that makes attribution harder. The report also flags a continued risk of destructive wiper malware and heavy use of AI-generated content in influence campaigns.

North Korea will keep escalating its highly successful and lucrative campaigns against cryptocurrency organizations and users. The report attributes to its actors the largest recorded cryptocurrency heist, valued at roughly 1.5 billion dollars, widely reported as the February 2025 Bybit exchange theft. It also points to continued use of techniques such as fraudulent hiring assessment pages and deepfake videos aimed at high-value employees. A growing concern is its IT worker scheme, where operatives use legitimate employment to access data and funds from inside target organizations.

For defenders, the practical message is consistent across all four. Strong, phishing-resistant identity, tight control over third-party access, and good monitoring of edge and infrastructure devices are what blunt these campaigns, the same fundamentals that defend against the AI and cybercrime threats above. Knowing them is the easy part. The harder challenge is operationalizing them at scale, across every human, machine, and agent identity in your environment.

What Is the Threat Model Behind These Predictions?

Strip away the three-theme framing and the report describes one threat model repeated across attacker types: get in through a trusted identity, credential, or third party, move through a layer defenders are not watching closely, and cause damage faster than the response process can react.

• Attacker capability. AI lowers the cost of convincing social engineering and fast reconnaissance for everyone, from lone criminals to state-sponsored teams, which is why volume rises across every category rather than one.
• Initial access. Phished or vished credentials, exposed edge devices, and compromised third parties dominate over software exploits as the way in, matching Google’s finding that most cloud breaches start with identity, not malware.
• Assets targeted. Attackers increasingly aim at the layer underneath what defenders monitor: the hypervisor under the virtual machine, the AI agent’s credential under the application, the third-party vendor under the primary target.
• Detection and response gap. Agent-speed and hypervisor-speed attacks compress the window to react from days to hours, so controls that depend on a human noticing in time are no longer sufficient on their own.

Every mitigation the report recommends, phishing-resistant MFA, workload identity, hypervisor hardening, vendor risk reviews, is a direct response to one of these four elements rather than a generic “improve security” recommendation.

What Are the Performance and Interoperability Trade-Offs of the Recommended Controls?

None of these controls are free, and a rollout that ignores the trade-offs stalls in production. Three deserve specific planning.

• Short-lived certificates increase rotation and issuance load. Moving from long-lived static credentials to certificates that expire in hours means your CA and issuance pipeline must handle far higher renewal volume without manual steps. Automated enrollment protocols (ACME, EST, or a managed CLM platform) are not optional at this scale; a manual process breaks the moment rotation drops below a day.
• Mutual TLS and workload identity add latency and legacy compatibility gaps. mTLS between every service adds a handshake cost per connection, and older systems, appliances, and some SaaS integrations do not support SPIFFE-style workload identity or client certificate authentication at all. Plan a phased rollout with a compatibility inventory rather than a flag-day cutover.
• Post-quantum hybrid handshakes increase payload size and negotiation time. Hybrid key exchange combining a classical algorithm (ECDHE) with a post-quantum one (ML-KEM/FIPS 203) produces larger TLS handshakes, which can matter for high-throughput or resource-constrained systems (IoT, embedded devices). Test interoperability against your actual client and load balancer stack before a broad rollout, since not every TLS library or hardware security module supports hybrid negotiation yet.

The right sequencing is usually: pilot on a low-risk service, measure the added latency and operational load, then expand by criticality tier rather than by convenience.

How Should You Build a 2026 Readiness Program?

1. Inventory every identity, human and non-human. Discover every certificate, key, API credential, service account, and AI agent identity across endpoints, applications, and cloud infrastructure before deciding what to fix.
2. Rank exposure by algorithm and credential lifetime. Flag which systems rely on long-lived static secrets, RSA/ECC certificates with long validity, or shared service accounts, since those are the exact patterns the forecast says attackers exploit.
3. Deploy phishing-resistant authentication for privileged and remote access. Replace or supplement one-time-code MFA with device-bound, certificate-based authentication for admins, remote access, and third-party connections.
4. Move workloads and AI agents to short-lived, verifiable identities. Pilot SPIFFE/SPIRE or an equivalent workload identity framework on one service, then expand by criticality.
5. Harden and monitor the infrastructure layer. Patch hypervisors on the same cadence as guest systems, monitor the virtualization fabric directly, and review which managed file transfer and edge devices sit exposed to the internet.
6. Start the post-quantum migration clock. Even though PQC is not this report’s focus, the identity infrastructure it recommends only holds up long-term if it is cryptographically agile enough to swap in FIPS 203/204/205 algorithms as CNSA 2.0 timelines approach.

What Do These Controls Look Like in Deployment?

Three concrete examples make the readiness steps above less abstract.

• An AI agent that reads customer support tickets and updates a CRM gets its own SPIFFE ID and a short-lived X.509 certificate scoped to exactly the CRM API calls it needs, issued and rotated automatically, instead of sharing the support team’s service account API key.
• A hypervisor cluster running production virtual machines gets EDR-equivalent monitoring on the management plane itself, patched on the same cycle as the guest operating systems, with the management interface segmented off the general corporate network.
• A crypto asset custody workflow moves private key generation and transaction signing into an HSM that never exposes the raw key, with a multi-party approval workflow in front of any transfer above a set threshold, closing the exact gap North Korea-linked actors exploited in 2025’s largest cryptocurrency theft.

Forecasted Threat, Readiness Action, and EC Service Mapping

Forecasted Threat	Organizational Readiness Action	EC Service
AI agents using shared, long-lived credentials	Issue short-lived, workload-scoped identities per agent; enforce least privilege and just-in-time access	PKI-as-a-Service, CertSecure Manager
Prompt injection and shadow agents	Inventory every agent, sandbox untrusted data, require human approval on high-risk actions	Encryption Advisory Services
Ransomware, extortion, and MFA-bypass vishing	Deploy phishing-resistant, certificate-based MFA for privileged and remote access	PKI Services, HSM-as-a-Service
Hypervisor and virtualization-layer compromise	Patch and monitor the management plane directly; segment from guest networks	Encryption Advisory Services
Nation-state credential theft and third-party abuse	Tighten vendor access reviews and enforce hardware-backed key custody	HSM Services, Compliance Advisory
Unknown cryptographic exposure (RSA/ECC dependence)	Run a full cryptographic discovery and inventory across the environment	CBOM Secure
Long-horizon quantum risk to current algorithms	Build a phased, crypto-agile migration roadmap to FIPS 203/204/205	PQC Advisory

What Are the Limitations of This Forecast?

Google’s forecast is grounded in real frontline telemetry, but it is still a forecast, not a guarantee. A few limitations are worth keeping in mind before treating any single prediction as certain.

• Predictions are probabilistic, not deterministic. The report describes what Google’s analysts expect based on current trajectories, and attacker priorities can shift faster than any annual report can track.
• Visibility is shaped by Google’s own customer base and Mandiant’s incident response caseload. Threats concentrated in environments Google and Mandiant do not see as often, certain regions, certain industries, may be underrepresented relative to their real-world prevalence.
• Statistics like the 2,302 Q1 2025 data leak site count reflect known, public leak sites. They do not capture victims who pay quickly enough to avoid public listing, or intrusions that never surface publicly at all.
• The report does not address post-quantum cryptography directly. EC’s PQC and crypto-agility recommendations in this post are our own extension connecting the report’s identity and credential themes to the separate, well-documented quantum migration timeline, not a claim the report itself makes.

Use the forecast to prioritize investment, not as a substitute for your own risk assessment of what actually runs in your environment.

What Would Encryption Consulting Recommend?

At Encryption Consulting, we offer comprehensive Encryption Advisory Services designed to enhance your organization’s data security posture. Our services help you identify and address encryption-related vulnerabilities, strengthen cryptographic protocols, and ensure full compliance with industry regulations and standards.

If you are wondering where and how to begin your post-quantum journey, Encryption Consulting is here to support you every step of the way.

Post-Quantum Advisory Services

We begin with a Cryptographic Discovery and Inventory, scanning your entire environment to identify certificates, keys, algorithms, and protocols across endpoints, applications, APIs, and infrastructure, building the baseline you need before any migration can begin. From there, we conduct a PQC Assessment to evaluate your exposure to quantum threats, identify RSA and ECC dependent systems, and deliver a prioritized report of vulnerable assets with risk severity ratings.

With that clarity, we develop a PQC Strategy and Roadmap: a phased migration plan aligned to your risk appetite, regulatory requirements, and long-term security goals, including cryptographic agility so your systems can adapt as standards evolve. We then support Vendor Evaluation and Pilot Testing, helping you select the right tools, run proof-of-concept tests, and validate interoperability before any full-scale rollout, before finally managing full implementation across your PKI, signing infrastructure, and TLS configurations with monitoring aligned to your long-term cryptographic health.

CBOM Secure

Encryption Consulting’s CBOM Secure gives a clear view of your cryptographic posture across environments. Instead of dealing with spreadsheets, manual OpenSSL outputs, or scattered configuration files, it shows which algorithms are in use, what needs to change for post-quantum security, and whether systems meet your security policy. It automates crypto inventories, checks TLS configurations, validates algorithms, and aligns policies so teams can move from discovery to action without guessing.

Compliance Advisory

For organizations facing overlapping regulatory pressure around identity, key management, and third-party risk, our Compliance Advisory services map the forecast’s identity-centric findings to frameworks like NIST CSF, DORA, and NIS2, so remediation work satisfies an auditor and closes a real attack path at the same time.

FAQ

What is the Google Cybersecurity Forecast 2026?

It is Google Cloud’s annual threat intelligence report, built from data gathered by the Google Threat Intelligence Group, Mandiant, and Google Security Operations. The 2026 edition organizes its predictions around three themes, AI, cybercrime, and nation-state activity, with identity as the connecting thread across all three.

What is prompt injection, and why is it hard to fix?

Prompt injection is an attack where hidden instructions inside data an AI model reads, such as a web page, an email, or a document, cause the model to take an action its owner never intended. It is hard to fix because it exploits how language models process instructions and data through the same channel, rather than a single patchable bug. OWASP lists it as LLM01, the top risk in its 2025 Top 10 for LLM Applications.

Why do AI agents need their own identities instead of shared credentials?

A shared service account with a long-lived API key gives every agent that uses it the same broad, standing access, so a single leaked credential exposes everything tied to it. Giving each agent its own managed identity, built on least privilege, just-in-time access, and short-lived, verifiable credentials, limits what any one compromised agent can do and keeps a clear record of which agent took which action.

Why do hypervisors matter so much in the 2026 threat landscape?

Hypervisors often run without endpoint detection and response, get patched late, and ship with insecure default settings, even though they host every virtual machine and application above them. A single successful compromise can let an attacker bypass the security tools inside every guest system and mass-encrypt the underlying virtual disks, taking down hundreds of systems in hours rather than the days a typical ransomware attack takes to spread.

Does the report cover post-quantum cryptography?

No. Google’s Cybersecurity Forecast 2026 focuses on AI, cybercrime, and nation-state activity, and does not address post-quantum cryptography directly. The connection to PQC and crypto-agility in this article is Encryption Consulting’s own analysis, tying the report’s identity and credential findings to the separate NIST post-quantum migration timeline.

How can organizations start preparing for post-quantum cryptography today?

Start with a cryptographic discovery and inventory to find every certificate, key, algorithm, and protocol in use, then assess which systems depend on RSA or ECC and would be exposed once quantum computing threatens them. From there, build a phased migration roadmap toward NIST’s finalized standards, FIPS 203, FIPS 204, and FIPS 205, aligned with CNSA 2.0 timelines, and design for cryptographic agility so the approach can adapt as guidance evolves.

Conclusion

Google’s Cybersecurity Forecast 2026 is really one story told three ways. AI hands both attackers and defenders new speed and scale. Cybercrime keeps cashing in through ransomware, crypto theft, and attacks on foundations like hypervisors and supply chains. Nation states pursue long-term goals by abusing trust and credentials. The thread tying them together is identity, and the quiet realization that in an agent-driven enterprise, identity belongs to software just as much as it belongs to people.

The good news is that the fundamentals still win. Treat every actor, human or machine, as a subject that must prove who it is and earn only the access it needs, for only as long as it needs it. Automate the certificates and keys that make that trust real. Keep your cryptography agile enough to evolve. For organizations facing long-term cryptographic risk, that also means beginning the migration to NIST’s finalized post-quantum cryptography standards (FIPS 203, 204, and 205) and aligning with CNSA 2.0 timelines. Do that, and the 2026 threat environment becomes something you can manage instead of something that manages you.

References

• Google Cloud / Google Threat Intelligence Group / Mandiant, Cybersecurity Forecast 2026
• Google Cloud, Cybersecurity Forecast 2026 full report (PDF)
• Google Cloud, Cloud CISO Perspectives: Our 2026 Cybersecurity Forecast report
• OWASP, 2025 Top 10 for LLM Applications
• NIST, SP 800-207: Zero Trust Architecture
• NIST, FIPS 203 (ML-KEM), FIPS 204 (ML-DSA), FIPS 205 (SLH-DSA)
• Gartner, 40 percent of enterprise apps will feature task-specific AI agents by 2026