The adoption of AI agents and large language models (LLMs) is transforming how organizations operate. Automation, decision-making, and digital workflows are advancing rapidly. However, this progress presents a paradox: the same agency that makes AI so powerful also introduces new and complex risks. As agents gain autonomy, they become attractive targets for a new class of threatsthat exploit intent, not just code.
Agentic Attacks: Exploiting the Power of Autonomy
Unlike traditional attacks that go after software vulnerabilities, a new wave of "agentic AI" attacks manipulates how agents interpret and act on instructions. Techniques like prompt injection and zero-click exploits don't require hackers to breach security perimeters. Instead, these attacks use the agent's access and decision-making capabilities to trigger harmful actions, often without users realizing it.
A zero-click attack, for example, can target automated browser agents. Attackers take advantage of an agent's ability to interact with web content without any user involvement. These attacks can steal data or compromise systems-all without a single click. This highlights the need for smarter, context-aware defenses.
Recent incidents show how serious this threat is:
- GeminiJack: Attackers used malicious prompts in calendar invites and files to trick Google Gemini agents. They were able to steal sensitive data and manipulate workflows without any user input.
- CometJacking: Attackers manipulated Perplexity's Comet browser agent to leak emails and even delete cloud data. Again, no user interaction was required.
- Widespread Impact: From account takeovers in OpenAI's ChatGPT to IP theft via Microsoft Copilot, agentic attacks now affect many LLM-powered applications in use today.
The Limits of Traditional Security
Legacy security tools focus on known threats. Pattern-based DLP, static rules, and Zero Trust models weren't built to understand the true intent behind an AI agent's actions. As attackers move from exploiting code to manipulating workflows and permissions, the security gap gets wider. Pattern-matching can't interpret context. Firewalls can't understand intent. As AI agents gain more access to critical data, the risks accelerate.
Semantic Inspection: A New Paradigm for AI Security
To meet these challenges, the industry is shifting to semantic inspection. This approach examines not just data, but also the intent and context of every agent action. Cisco's semantic inspection technology is leading this change. It provides:
- Contextual understanding: Inline analysis of agent communications and actions to spot malicious intent, exposure of sensitive data, or unauthorized tool use.
- Real-time, dynamic policy enforcement: Adaptive controls that evaluate the "why" and "how" of each action, not just the "what."
- Pattern-less protection: The ability to proactively block prompt injection, data exfiltration, and workflow abuse, even as attackers change their methods.
By building semantic inspection into Secure Access and Zero Trust frameworks, Cisco gives organizations the confidence to innovate with Agentic AI. With semantic inspection, autonomy doesn'thave to mean added risk.
Why Acting Now Matters
The stakes for getting AI security right are rising quickly. Regulatory demands are increasing, with the EU AI Act, NIST AI Risk Management Framework, and ISO/IEC 23894:2023 all setting higher expectations for risk management, documentation, and oversight. The penalties for non-compliance are significant.
At the same time, AI adoption is surging-and so are the risks. According to Cisco's Cybersecurity Readiness Index, 73 percent of organizations surveyed have adopted generative AI, but only 4% have reached a mature level of security readiness. Eighty-six percent have reported experiencing at least one AI-related cybersecurity incident in the past 12 months. The average cost of an AI-related breach now exceeds $4.6 million, according to the IBM Cost of a Data Breach Report.
For executive leaders, the path forward is clear: Purpose-built semantic defenses are no longer optional technical upgrades. They're essential for protecting reputation, ensuring compliance, and maintaining trust as AI becomes central to business strategy.
Securing the Future Starts Today
AI's rapid evolution is reshaping business models, customer expectations, and the competitive landscape. It's also transforming how organizations operate and deliver value. AI agents bring real business value, but their growing autonomy demands a new security mindset.
Organizations must understand not just what agents do, but why they do it. Building semantic security focused on intent and context is essential. This approach paves the way for realizing AI's full potential. Acting now positions your organization for AI-driven growth and long-term success.