Trade Policy Shifts Expose Cyber Gaps—Use AI to Close

Trade negotiations move fast. Nation-state attackers don’t slow down to match the news cycle.

The latest debate in Washington—whether trade concerns are quietly outweighing cybersecurity priorities—matters for a simple reason: adversaries plan in years, while policies often swing in quarters. Reports that sanctions tied to the Salt Typhoon telecom intrusions may be eased, alongside signs of flexibility around exporting high-end AI chips, are being read by many security leaders as a signal: cyber consequences are negotiable.

From an AI in Defense & National Security perspective, the uncomfortable truth is that diplomacy can reduce friction, but it doesn’t reliably reduce intrusions. If you’re responsible for enterprise security, national security systems, or critical infrastructure, the practical question is: How do you keep detection and response consistent when geopolitical priorities aren’t? The answer is “deterrence by denial” at scale—and AI is how you get there.

When trade becomes a cyber variable, defenders lose

When cyber tools (sanctions, export controls, regulatory pressure) get folded into broader trade and diplomatic bargaining, defensive expectations become unstable. You can’t build a multi-year security program on top of policy signals that might change after the next negotiation round.

Here’s the operational impact I see most often:

• Mixed signals to adversaries: If consequences appear reversible, attackers treat them as a cost-of-business line item.
• Procurement whiplash: Programs get funded, paused, re-scoped, then restarted—often with new stakeholders and new priorities.
• Compliance gaps: If telecom or critical infrastructure rules are rolled back, you get uneven security maturity across the ecosystem.

Salt Typhoon is a good example of why this matters. The campaign started with telecom and ISP targets and expanded over time, with reporting suggesting hundreds of victims across dozens of countries. That’s what persistent access looks like: attackers get in, stay in, and reuse the footholds.

Policy may shape the headlines, but persistent access shapes your Monday morning.

Sanctions aren’t a shield

Sanctions can be appropriate and sometimes necessary. But as a primary deterrent in cyberspace, they’re limited.

Why?

1. Attribution and timing lag: By the time sanctions land, the operation has usually matured and the access has spread.
2. Asymmetric incentives: The value of espionage (or prepositioning in infrastructure) can exceed the economic pain imposed.
3. Plausible deniability and proxies: Contractors, front companies, and “patriotic hackers” muddy the accountability chain.

This is why seasoned practitioners keep returning to a blunt but accurate stance: you can’t sanction your way out of a compromise.

“Deterrence by denial” is the only approach that scales

Deterrence by denial means making it hard to succeed and hard to stay hidden. It’s the opposite of hoping an attacker behaves; it’s building systems where success is expensive and time-limited.

In national security terms, deterrence by denial is what you do when you assume:

• adversaries will continue intrusions regardless of diplomatic posture,
• offensive cyber operations will remain a constant tool of statecraft,
• critical infrastructure will remain a prime target.

For CISOs and federal program owners, this translates into five non-negotiables:

1. Inventory that reflects reality (assets, identities, dependencies)
2. Strong identity controls (MFA, least privilege, continuous access evaluation)
3. Fast patching and compensating controls (especially at the edge)
4. Telemetry you can trust (endpoint, network, cloud, identity logs)
5. Response that works at machine speed (containment, isolation, rollback)

The issue: doing all of that manually across a modern environment is a losing strategy. That’s where AI becomes less “nice to have” and more “you won’t keep up without it.”

Why AI-driven cybersecurity is built for policy volatility

AI-driven cybersecurity is valuable here for one main reason: it makes security performance less dependent on stable policy and more dependent on measurable operational capability.

If trade negotiations soften consequences or regulations fluctuate, your AI-enabled detection and response should still:

• spot abnormal access patterns,
• connect low-signal events into a coherent incident story,
• contain threats before persistence is established.

What AI does better than humans in nation-state-style incidents

Nation-state campaigns tend to win on patience and volume: lots of subtle actions across many systems over long periods. AI helps because it can operate continuously across that scale.

Concretely, modern security AI (when implemented well) improves:

• Anomaly detection across identities and endpoints: spotting unusual service account behavior, rare admin actions, impossible travel, and abnormal token usage.
• Behavioral baselining: distinguishing “weird but normal for finance quarter-end” from “weird and malicious.”
• Alert triage and clustering: merging 200 noisy alerts into 3 incident threads you can actually investigate.
• Automated containment workflows: disabling suspicious sessions, isolating hosts, forcing re-authentication, rotating secrets.

One stance I’ll defend: AI isn’t replacing analysts; it’s replacing the part of the job that attackers exploit—slow correlation and slow response.

The hidden win: AI makes telecom-style compromises harder to reuse

The Salt Typhoon-style target set (telecoms, ISPs, managed networks) is especially sensitive because compromise can provide access to downstream organizations.

AI helps limit reuse by:

• detecting lateral movement patterns earlier,
• identifying “new persistence” artifacts (scheduled tasks, services, remote management abuse),
• surfacing suspicious admin tool usage (living-off-the-land behaviors),
• prioritizing response based on blast radius (which systems provide transit to others).

This matters because nation-state actors love infrastructure that gives them optionality. AI reduces that optionality by shrinking dwell time.

Practical playbook: build AI-assisted denial in 90 days

Most teams don’t need a moonshot. They need a short, disciplined plan that improves detection and response before the next policy swing—or the next intrusion.

Here’s what works in practice.

Step 1: Fix your “detection inputs” before buying more AI

AI systems are only as useful as the signals they can see. Prioritize these telemetry sources first:

• Identity provider logs (authentication, conditional access, risky sign-ins)
• EDR telemetry (process trees, script execution, persistence attempts)
• Network DNS and proxy logs (command-and-control patterns)
• Cloud control plane logs (IAM changes, key creation, suspicious API calls)

If you’re missing any of these, AI will still produce output—but it’ll be less reliable, and your team will stop trusting it.

Step 2: Use AI to reduce mean time to understand (MTTU)

Most orgs track MTTR. Fewer track the earlier bottleneck: MTTU—how long it takes to understand what’s actually happening.

AI-assisted investigations should produce:

• a time-ordered narrative (“what happened first, second, third”),
• affected identities and assets,
• likely objectives (espionage vs disruption vs prepositioning),
• recommended containment steps with estimated impact.

If your tools can’t do that, you’ll keep burning senior analysts on basic correlation.

Step 3: Automate containment for a narrow set of high-confidence cases

Automation fails when it’s too broad. Start with the actions that are reversible and low-risk:

• isolate endpoint from network,
• disable a token/session,
• force password reset and revoke refresh tokens,
• quarantine an email campaign,
• block known malicious domains/IPs (with review gates).

Then add governance:

• require human approval for actions that can cause downtime,
• log every automated step with who/what triggered it,
• run quarterly “automation fire drills.”

Step 4: Apply AI to supply chain and software provenance

The source article makes a key point: supply chain compromise can’t be solved with sanctions.

Use AI-assisted controls to improve software trust:

• detect anomalous dependency updates (sudden maintainer changes, unusual version jumps),
• score build and release risk based on behavior, not just signatures,
• monitor for credential exposure patterns in CI/CD.

This is where enterprise security and national security overlap sharply: software supply chains are strategic terrain.

Common executive questions (and straight answers)

“If sanctions and regulations aren’t reliable, what should we measure?”

Measure operational denial:

• MTTD/MTTR segmented by identity, endpoint, and cloud
• Dwell time (how long attackers persist before eviction)
• Coverage (percent of assets and identities producing usable telemetry)
• Containment automation rate (with low false-positive impact)

These metrics stay relevant no matter who’s negotiating what.

“Won’t AI increase risk if it makes the wrong call?”

It can—if you automate everything blindly. The safer model is:

• AI suggests, humans approve (for high-impact actions)
• AI acts automatically only on narrow, reversible actions
• continuous tuning based on post-incident review

“Is this mainly a government problem?”

No. Telecom compromises and critical infrastructure intrusions create downstream risk for every enterprise that depends on connectivity, cloud, and managed services—which is basically all of them.

What security leaders should do next

Trade priorities will keep shifting. Offensive cyber operations will keep running. That tension isn’t going away in 2026.

If you take one thing from the Salt Typhoon debate, let it be this: cyber defense can’t be seasonal or transactional. Your posture has to be consistent even when policy isn’t—and AI-driven cybersecurity is one of the few practical ways to stay consistent at scale.

If you’re evaluating AI for security operations, start small but serious: pick one environment (identity + endpoints), instrument it properly, and demand measurable improvements in MTTU, dwell time, and containment speed.

What would change in your risk profile if your team could contain suspicious access in minutes—before it becomes a months-long nation-state foothold?