Businesses do not need to plan for a “Skynet” scenario to take AI security seriously. Generative AI can help attackers carry out familiar attacks, while AI applications and agents create new ways to expose data or systems. Reduce those risks first with scoped permissions, strong identity controls, threat modeling and monitoring; then consider specialized tools for discovering, testing or protecting AI workloads. No product can guarantee protection.
What are the real AI-related cybersecurity risks for businesses?
NIST describes two related information-security risks: generative AI may lower barriers to offensive cyber activity, and AI systems themselves create an attack surface. In its July 2024 Generative AI Profile, NIST identifies prompt injection and data poisoning among the vulnerabilities to consider. It also notes the need to protect AI system availability and the integrity and confidentiality of code, training data and model weights.
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These are risks to manage, not evidence that a Skynet-like event is likely or that every business faces the same exposure. The available sources do not establish a probability for such an event or quantify the overall business impact of AI cyber threats.
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Generative AI may ease or automate parts of offensive activity, including hacking, malware and phishing. That does not make every AI-assisted attempt novel: businesses still need the cybersecurity controls used to protect accounts, devices, networks and data.
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- RELIABLE CUSTOMER SUPPORT: FortiCare Premium ensures high-quality support and service continuity.
- EFFECTIVE PROTECTION: Employs advanced filtering technologies to safeguard against sophisticated threats.
AI systems can be attacked through their inputs and connections
Prompt injection is more than a chatbot producing an odd answer. Malicious instructions can be supplied directly or placed in material an AI application retrieves. NIST reports demonstrations against connected large language model applications in which attacks could steal proprietary data or run malicious code remotely. The risk is especially important when an AI agent can access sensitive information or use tools on a user’s behalf.
What should a business do before buying an AI security tool?
Start with the AI systems already in use, including agents and connected services. Map where they run, what data they can reach, which tools they can invoke and which identities authorize those actions. A policy or risk framework helps organize decisions; it does not replace technical controls that enforce access or monitor activity.
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- Refer instruction manual for troubleshooting steps.
Apply controls to agentic AI
In May 2026, CISA and international partners published guidance for the secure adoption of agentic AI. Its recommendations translate into practical checks:
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- Give an agent only the permissions needed for its assigned task, and avoid broad access to sensitive systems or data.
- Use strong identity management and layered defenses around agents and the resources they can reach.
- Threat-model an agent and its connections before deployment.
- Monitor use continuously and assess safeguards regularly.
This guidance supports careful adoption; it does not mean every organization needs a dedicated AI security platform.
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- XGS 118 with 1 Year Xstream Protection - Next-generation firewall appliance with Xstream Protection subscription providing zero-day defense, cloud sandboxing, email filtering, intrusion prevention, and advanced reporting, managed through Sophos Central for unified policies and reporting.
- 9 x 2.5 GE copper ports and 1 SFP fiber port, delivering up to 15.5 Gbps firewall performance for mid sized organizations.
- Zero day protection with cloud sandboxing, email filtering, and advanced reporting for full enterprise coverage.
- TLS inspection and next generation intrusion prevention block hidden threats in encrypted traffic and stop sophisticated attacks.
- Includes Xstream Protection – Advanced security bundle with zero-day protection, cloud sandboxing, email filtering, and automated threat response, providing full coverage against the most sophisticated cyberattacks.
Use a risk-management framework for governance
NIST’s AI Risk Management Framework is voluntary guidance for managing AI risks across design, development, deployment and evaluation. Its Generative AI Profile applies that approach to generative AI. NIST’s framework page said AI RMF 1.0 was being revised as of October 7, 2026; check the current status before using it as a basis for policy.
Which software tools address AI-specific security needs?
Vendor documentation describes products for different parts of the problem: finding AI workloads, assessing them before deployment, or inspecting activity at runtime. The descriptions below are vendor claims, not independent comparative tests or proof of outcomes. Product fit depends on where AI runs, what agents can access and which security controls the organization needs.
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- UTP SECURITY FEATURES: Offers protection from advanced threats with DNS filtering, URL filtering, video filtering, and controls against botnets.
- IDEAL FOR SMALLER SETTINGS: Best suited for small to mid-sized businesses needing reliable security without the complexity of larger systems.
- CONTINUOUS SUPPORT AND MAINTENANCE: FortiCare Premium ensures that technical help is readily available to manage and troubleshoot issues.
- COMPACT AND EFFECTIVE: Provides a powerful, yet compact security solution that effectively protects against a wide range of cyber threats.
| Tool | Vendor-described capabilities | Potential fit and qualification |
|---|---|---|
| Microsoft Defender for Cloud AI security posture management | Microsoft describes AI workload discovery, an AI bill of materials, posture recommendations and attack-path analysis. Its documentation lists discovery across Azure OpenAI, Azure AI Foundry, Azure Machine Learning, Amazon Bedrock and Google Vertex AI. | Potentially relevant when a business needs cloud AI workload inventory and posture management. Microsoft says agent-level discovery and posture for Foundry and third-party cloud agents require Microsoft Agent 365 effective July 1, 2026. |
| Microsoft Defender for Endpoint AI agent runtime protection | Microsoft describes inspection of user prompts, agent tool calls and tool responses for supported local agents, with audit and block modes. | Potentially relevant when local agents can read files or invoke tools. Microsoft marks the feature Preview and recommends beginning in audit mode to validate detections before enabling blocking. Supported-agent coverage and licensing should be checked against current documentation. |
| Cisco AI Defense | Cisco describes AI asset discovery, supply-chain scanning, algorithmic testing and red teaming, plus runtime protections for prompts, responses and agent/MCP interactions. | Potentially relevant to organizations evaluating discovery, pre-deployment testing and runtime controls. The stated capabilities are Cisco’s product claims; they do not establish independent efficacy or universal suitability. |
How should you choose between AI security products?
Compare tools against your environment and security objectives rather than treating “AI security” as a single feature. A cloud inventory tool, a pre-deployment testing workflow and runtime enforcement solve different problems.
- Locate the workloads. Identify whether applications and agents run in cloud services, on local devices or across both. Check that a product covers the specific services and agent types in use.
- Decide which control is missing. Determine whether you need discovery, posture management, pre-deployment testing, runtime protection or a combination. Confirm what the tool actually inspects and whether it can audit or block.
- Review agent permissions and identities. Verify that agents use controlled identities and limited access. A monitoring product is not a substitute for restricting what an agent can do.
- Check operational fit. Assess integration with existing security monitoring and incident response, along with deployment requirements, data handling and licensing.
- Validate before enforcement. Where a product provides an audit mode, examine detections and likely operational effects before turning on blocking. For preview features, verify maturity and supported coverage before relying on them.
Vendor features and availability can change quickly. Microsoft last updated its Defender for Endpoint runtime documentation on September 16, 2026, and labels that feature Preview. Confirm current product documentation, supported services and licensing before making a purchase or deployment decision.
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