Generative AI—A Double-Edged Sword in Security

Summary: 

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Generative AI’s impact is continually expanding. In recent years, it has begun to demonstrate unprecedented capabilities. It can now create tools to write code, generate images, simulate voices, and compose human-like text that is affecting every industry, including security. This power is not without risk. The same power that can create an educational video can also be used to make deepfakes to spread misinformation. In security, the same power that enables faster threat detection and response can also be leveraged to create more sophisticated phishing attacks, develop malware, and exploit security vulnerabilities.

As organizations rush to adopt generative AI, leaders must pause and assess both sides of this double-edged sword. In this article, we examine the dual impact of generative AI on security, highlighting its benefits, exposing its threats, and offering practical recommendations for navigating this rapidly evolving terrain.

Benefits of Generative AI in Security

While generative AI poses real and growing risks, it also holds the potential to strengthen security operations when used responsibly. Here are a few key ways generative AI is already helping security teams work faster, smarter, and more effectively:

1. Accelerated Threat Detection and Investigation

Generative AI can analyze massive volumes of data—logs, alerts, and communications—far faster than human teams alone. What would take a security guard hundreds, if not thousands of hours to comb over, AI can do around the clock in real-time, almost instantly. It can identify unusual patterns, summarize threat intelligence, and even draft incident reports. This enables quicker responses to threats and reduces the window of opportunity.

2. Security Automation and Scripting

Generative AI can help security teams automate repetitive and time-consuming tasks by writing code and scripts tailored to specific needs. For example, it can write Python or PowerShell scripts (code) to automate routine log analysis, user behavior tracking, or system audits. It can also create custom firewall rules, access control policies, and cloud security configurations based on best practices.

In incident response scenarios, generative AI can suggest or generate baseline playbooks—step-by-step guides that outline how to contain a threat, remediate damage, and restore normal operations. These playbooks, which once took hours or days to draft manually, can now be produced in minutes and tailored to an organization’s environment based on what the AI has observed from the site. 

By automating this work, teams can become more efficient as they focus their energy on more complex, strategic challenges like risk assessment, threat hunting, and long-term defense planning.

3. Synthetic Training Environments

Sometimes the best way to know the efficacy of your system is to test it. It is better and safer to do that internally than wait until a real threat appears and see if your team is ready. AI can generate realistic, synthetic data to simulate cyberattacks and physical breaches, allowing teams to test defenses without exposing sensitive systems. 

4. Clearer Communication and Faster Decision-Making

Generative AI can take complex data—like system logs, threat reports, or attack timelines—and turn it into clear, easy-to-understand summaries. This helps technical teams explain what’s happening to non-technical stakeholders, such as executives or department heads, without having to manually translate every detail.

For example, during a security incident, AI can quickly generate a summary of the threat, what systems are affected, what actions have been taken, and what still needs to be done. This makes it easier for leaders to make fast, informed decisions and keeps everyone aligned.

5. Increased Peace of Mind Through Intelligent Monitoring

Generative AI, when integrated into surveillance systems, can analyze live camera feeds and sensor data in real time, freeing up security personnel from the exhausting task of constant manual monitoring. Instead of staring at screens for hours, teams can rely on AI to detect unusual behavior, flag potential threats, and send proactive alerts when something needs human attention.

This shift improves situational awareness, allowing people to focus on higher-value responsibilities. It provides peace of mind, knowing that a smart, agentic security system is always watching, learning, and ready to act, without the burnout or blind spots that come from relying on humans alone.

Risks and Security Implications of Generative AI

As powerful as generative AI can be in strengthening security, it also introduces vulnerabilities. These risks cross both digital security and physical threats. The best systems require a proactive and layered defense plan to ensure your business is truly secure.

Cybersecurity Risks

Phishing and Social Engineering

Generative AI can create hyper-realistic phishing emails that are nearly indistinguishable from real messages. It can mimic tone, style, and branding to increase the likelihood of successful attacks. In more advanced cases, attackers even use AI-generated voice recordings or deepfake videos to impersonate executives or vendors, manipulating employees into sharing sensitive information. 

Malware and Exploit Development

AI’s strong pattern recognition abilities allow it to test vulnerabilities in a security system. Attackers can then leverage this information. Using AI to generate malicious code, they can target the vulnerabilities that the AI found. What once required deep technical knowledge can now be created with minimal expertise.

Data Leaks

Generative AI can sometimes reveal sensitive information without meaning to—especially if it was trained on private or unfiltered data. In some cases, attackers can trick the AI into giving up confidential details, like internal documents, passwords, or personal information. These types of attacks create serious privacy and security concerns for any organization using AI tools without proper safeguards.

Physical Security Threats

Spoofing and Deepfakes

In physical security, deepfake technology can be used to spoof identities and bypass facial recognition or voice authentication systems. A synthetic video or AI-generated voice can be enough to trick access controls, impersonate staff, or fool security protocols.

Synthetic Surveillance Bypass

Generative AI can be used to trick security cameras and other smart surveillance systems. For example, someone might wear special patterns or move in certain ways that confuse the AI, making it unable to recognize faces, people, or dangerous activity. These kinds of tactics can create blind spots that allow threats to go undetected.

Key Strategies for Managing AI Risks

To safely harness the power of generative AI while minimizing its risks, organizations must take a proactive and collaborative approach. Below are key recommendations for securing AI use across your operations:

AI Monitoring and Guardrails

Establish clear policies around how generative AI tools are used within your organization. Define who can access them, what types of data can be entered, and where outputs can be applied. It may be important to implement monitoring systems that can detect unusual usage patterns, such as an employee suddenly generating large amounts of code, accessing sensitive data, or requesting restricted information. Early detection of misuse can prevent a small issue from becoming a major incident.

Security-First AI Development

To limit breaches of sensitive data, organizations must train models on carefully vetted datasets and weave in safeguards that can detect bias, inappropriate outputs, or attempts to exploit the system. Regularly test agentic security models for vulnerabilities such as prompt injection or data leakage, and ensure AI outputs are reviewed, especially in high-risk environments like surveillance, authentication, or customer data processing.

Cross-Functional Readiness

Agentic security affects an entire organization: legal, HR, compliance, and executive teams should all be involved in assessing and managing AI-related risks. Develop a shared understanding of potential scenarios, and provide training so employees across departments know how to spot red flags and stop breaches before they happen. By ensuring your team is on the same page, you create a more resilient and responsible AI strategy.

Conclusion

Generative AI offers new tools for detection, response, and efficiency, while also introducing complex and evolving threats. As this technology becomes more accessible, the risks tied to misuse, manipulation, and exploitation are growing just as fast as the benefits.

For security teams, the challenge is to strike the right balance: embracing innovation while putting safeguards in place to prevent it from becoming a security risk. By implementing strong usage policies, monitoring for misuse, and fostering cross-functional awareness, organizations can unlock the power of AI confidently and responsibly.

At LiveView Technologies (LVT), we’re committed to using AI in ways that enhance safety, protect privacy, and deliver peace of mind. Our solutions combine AI-powered analytics with responsible design, ensuring you get the benefits of cutting-edge technology without sacrificing control or visibility.

Want to learn more about how LVT uses AI to protect your people, property, and peace of mind? Contact us today to schedule a demo or speak with a security expert at lvt.com.