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2026 AI Threat Landscape Report

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The 2026 AI Threat Landscape Report explores insights from over 500 security professionals on emerging AI threats, including agentic AI, supply chain attacks, and prompt injection, highlighting the critical need for enhanced AI security measures.

  • Year2026
  • Editionthird annual
  • Sample250 IT and security leaders
  • AccessEmail-gated
  • FormatPDF
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The 2026 AI Threat Landscape Report provides a comprehensive analysis of the evolving threats posed by AI technologies. With contributions from over 500 security professionals, this report delves into the challenges organizations face as AI transitions from a supportive role to an autonomous actor in business processes. It highlights the increasing reliance on AI for revenue generation, customer experience, and core operations, while many security frameworks remain outdated, primarily designed for traditional software controls.

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Key findings reveal a significant gap between AI deployment and security measures. While foundational controls are in place, the report emphasizes that agentic AI requires more than just secure deployment; it demands continuous accountability, runtime visibility, and tailored security controls. As AI systems become more autonomous and interconnected, the risks associated with their use escalate, necessitating a proactive approach to security.

The report identifies five critical threat areas that security teams must monitor: data poisoning, AI supply chain attacks, prompt injection, memory and RAG poisoning, and model evasion. Each of these areas presents unique challenges that can compromise AI model integrity and functionality. Furthermore, the report documents real-world instances of AI misuse, including deepfakes, political disinformation, and automated cybercrime, underscoring the urgent need for robust AI security frameworks.

To address these challenges, the report advocates for treating AI security as a fundamental business and regulatory requirement rather than a mere feature. It encourages organizations to move beyond basic guardrails to implement comprehensive runtime monitoring and adversarial testing. By reassessing third-party AI risks and aligning governance with business impact, organizations can better prepare for the complexities of AI security in an increasingly digital landscape.

  • CategoryAI Cybersecurity Tools

  • Publisher: HiddenLayer

  • Published Year: 2026

  • Data Sources: Survey data from 500+ security professionals

  • Report Type: Threat Landscape Report

  • AI Security Assessment
  • Threat Monitoring
  • Risk Management
  • Compliance Auditing
  • Incident Response Planning

From HiddenLayer

A feature of HiddenLayer | Total AI Security.

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