Friend or Foe? AI’s Double-Edged Sword in Cybersecurity

Christopher Souza | CEO

Artificial Intelligence (AI) is rapidly transforming the cybersecurity landscape by acting as both a powerful shield and a potential vulnerability. While AI has the ability to strengthen defenses with automation and threat detection, it also introduces new risks from cybercriminals leveraging the same technology for more sophisticated attacks unlike anything done before. But just like any tool, AI’s impact depends on how it’s used, making it essential to strike a balance between this double-edged sword of innovation and risk. AI is here to stay, and those who learn to harness its potential while mitigating its risk will be best positioned to navigate our evolving security landscape. TSI has come up with this guide to help your organization understand more about AI and what it means for cybersecurity as a whole.

AI’s POSITIVE Impact on Cybersecurity

Advanced Threat Detection: AI is a pivotal asset for organizations to transform their reactive cybersecurity measures into proactive strategies. By employing machine learning algorithms, AI systems like behavioral analytics platforms, anomaly detection systems, and threat intelligence software can quickly analyze massive amounts of data to detect anomalies indicative of cyber threats like malware and phishing attempts, leading to faster and more accurate threat detection.

Proactive measures are becoming more and more of a necessity in today’s cyber climate as an estimated 3.4 billion phishing emails are sent out every day, underscoring the critical need for robust cybersecurity measures. Understanding and integrating AI capabilities into cybersecurity tools are essential for any organization aiming to bolster their defenses against these threats.

Automated Incident Response: AI is transforming cybersecurity by automating incident response processes, allowing for immediate action when a threat is detected helping minimize damage before human teams can intervene. Advanced Security Information and Event Management (SIEM) systems, Extended Detection and Response (XDR) solutions, and Endpoint Detection and Response (EDR) platforms enable AI-driven automation to proactively isolate infected systems, block malicious IPs, and initiate remediation steps—ensuring unparalleled speed of action.

Timeliness is critical when responding to cyber threats, as the average data breach costs U.S. companies $4.45 million per incident, with costs escalating the longer a breach goes undetected. The faster an organization can detect, contain, and respond to a threat, the lower the financial and operational impact. For organizations with the DFARS 7012 (CMMC) requirements, AI-powered incident response tools are not just beneficial—they are essential. These organizations have a contractual obligation to report breaches to the DoD within 72 hours, making real-time monitoring, rapid detection, and automated response capabilities indispensable for compliance and security.

Predictive Analytics: Through predictive analytics, AI can forecast potential vulnerabilities and attack vectors by analyzing historical data and identifying emerging threat trends. This approach lets organizations rest assured that their defenses remain ready for whatever comes their way.

Behavioral analytics platforms use AI to monitor user activity, detecting unusual login attempts or deviations in access patterns that could indicate credential theft or insider threats. Threat intelligence solutions analyze vast amounts of global cybersecurity data to predict which attack methods hackers are likely to use next. Meanwhile, automated risk assessment tools evaluate system weaknesses and suggest mitigation strategies before vulnerabilities can be exploited. Predictive AI in next-generation firewalls (NGFWs) can also identify and block zero-day threats before they execute, while AI-powered email security solutions preemptively recognize and filter out advanced phishing attempts by analyzing linguistic patterns and sender behaviors.

There is evidence of these services being put into practice, as well. For example, Darktrace, a British cybersecurity firm, has utilized unsupervised AI machine learning to establish a baseline “pattern of life” for every company network, device, and user. Darktrace’s AI can detect and respond to anomalies in real leveraging the previously learned normal behaviors of the organization, and can predict when something isn’t right. Such applications demonstrate AI’s capability to anticipate and prevent cyber threats, significantly enhancing organizational security posture.

AI’s NEGATIVE Impact on Cybersecurity

AI-Powered Cyber Attacks: Cybercriminals are increasingly utilizing AI to enhance the sophistication of their attacks, enabling these characters to craft phishing emails that are far more convincing by simulating personal writing styles, analyzing target behavior, and adapting to spam-detection systems. Just think about how many spam emails wind up in your email inbox and are not filtered out by your actual spam filter. These technological advancements in attacks pose a serious threat to every member of your organization, highlighting the importance of strengthening security with end-user security awareness training. As AI-driven phishing tactics become more sophisticated, educating employees on recognizing suspicious emails, implementing multi-factor authentication, and enforcing strict access controls are critical steps in minimizing the risk of a breach. Studies show that organizations that provide regular end-user security training reported a 60% improvement in awareness of security risk and a 40% decrease in the number of harmful links clicked by users.

Additionally, AI facilitates large-scale, automated attacks, enabling criminals to target thousands of organizations with higher efficiency and precision. This combination of personalization and scale makes these threats significantly more difficult to defend against proving that AI is not just a tool for protection—it’s also a weapon when placed in the wrong hands, capable of outpacing traditional security measures. Such an example can be seen in the 2023 MOVEit Data Breach where the sensitive data of thousands of organization were exposed by a cybercriminal group using AI-disguised ASP.NET files to automate data theft and evade detection.

Deepfake & Social Engineering Threats: AI-generated deepfakes—manipulated audio or visual content—represent a growing risk in social engineering attacks. These sophisticated forgeries can convincingly impersonate trusted individuals in an organization, like CEOs, family members, or colleagues, to manipulate the victim into divulging sensitive information or authorizing fraudulent transactions. In early 2024, New Hampshire voters received robocalls featuring an AI-generated voice mimicking former President Biden; urging them not to vote in the Democratic primary, and more recently, deepfake videos emerged targeting current President Donald Trump and Elon Musk by depicting them in various scenarios meant to deceive the public and tarnish reputations. AI’s ability to generate these realistic videos and audio clips with minimal resources makes deepfakes a powerful tool for cybercriminals seeking to bypass traditional security measures.

In 2024, the British engineering firm Arup experienced one of these attacks firsthand when criminals impersonated existing employees’ voices, signatures and deepfaked images to deceive a staff member into transferring over $33 million into multiple accounts. Incidents like this highlight the increasing threat posed by AI-generated deepfakes and the necessity for enhanced cybersecurity measures to protect against such hard-to-detect attacks.

Increased Attack Surface: The integration of AI into various business processes can inadvertently expand the attack surface, and if AI systems are not properly secured, you better believe they are prime targets for cybercriminals. AI-powered tools like chatbots or automated customer service platforms may be vulnerable to attackers who can use them to gain unauthorized access to systems or sensitive data. Adversaries might also exploit the normally helpful predictive capabilities of AI so that they can anticipate organizational security measures and make it easier to bypass traditional cybersecurity defenses. For example, in September 2024, a hacker exploited vulnerabilities in OmniGPT, a popular AI chatbot and productivity platform exposing the personal data of over 30,000 users, including emails, phone numbers, and over 34 million lines of conversation logs, underscoring how dangerous AI-powered tools can be if compromised.

Another recent trend is the use of AI to generate physical mail that appears legitimate only to trick recipients into scanning a malicious QR code that leads to credential theft, malware infection, or even ransomware deployment. These AI-generated letters bypass email security filters and rely on social engineering tactics in the real world.

Data Leakage Risks: Employees may unknowingly input proprietary data into AI-powered chatbots or AI automation tools, making it accessible beyond the organization. Many AI tools use user inputs for training data, which means any sensitive company information entered into these platforms could potentially be exposed to others. This creates significant risks that include the potential leakage of confidential business strategies, trade secrets, intellectual property, and more. Businesses will have to establish strict policies governing AI use to ensure their employees understand the risk of sensitive data to try and combat this. Web filtering and access controls also can help prevent unauthorized AI interactions that could compromise critical company information.

Keeping Things Balanced

To harness the benefits of an exciting new technology like AI while mitigating the many risks that come with it, organizations should consider the following strategies:
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• Implement Robust Security Measures: Since AI systems require religious security protocols, it’s best to keep them healthy and secured against potential threats by continuous monitoring, doing vulnerability assessments, and conducting regular updates and software patching. As part of our standard MSP practice, we handle these critical tasks for our clients, including continuous monitoring, vulnerability assessments, and regular updates/software patching.
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• Continuous Monitoring & Adaptation: Regularly update AI models to recognize new threat patterns and adapt to evolving cyber-attack methodologies. This means integrating real-time data analysis to spot abnormal behaviors quickly and efficiently. We handle these tasks for our clients by integrating real-time data analytics to quickly and efficiently detect abnormal behaviors.
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• Human-AI Collaboration: AI alone cannot replace human judgment in complex security scenarios. It’s vital to combine AI capabilities with human expertise to enhance decision-making processes in threat detection and response so that high-risk situations are handled correctly. We provide expert-driven security solutions and end-user awareness training to help organizations strengthen their defenses as part of this collaboration effort.
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• Ethical AI Practices: As exciting as AI is, ethical considerations should be at the forefront when deploying AI in cybersecurity. It’s crucial to ensure AI systems respect privacy rights, operate transparently, and are free from biases. To maintain public trust, we must all work together to prevent AI misuse and have accountability measures set in place to ensure that.
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• Choosing Reputable AI Platforms & Stakeholder Involvement: If organizations decide to integrate AI into their operations, it’s crucial that they’re using a reputable AI platform or service. Not all AI tools are the same. Relying on unverified AI services can introduce vulnerabilities or lead to compliance issues. Due diligence in assessing factors like data privacy policies, security features, and regulatory compliance is key.

  Additionally, involve your key stakeholders, including HR, IT, Finance, Public Affairs, and even the Board of Directors in the discussion about AI implementation. This ensures a well-rounded approach to risk assessment and strategic decision-making. The fewer blind spots an organization can have when implementing AI, the better.
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TSI & Next-Gen Cybersecurity:

At Technical Support International (TSI), we recognize the transformative potential of AI in cybersecurity. Many of our Managed Security Service (MSSP) solutions leverage advanced AI and deep learning technologies to provide continuous protection against today’s most sophisticated cyber threats. By staying informed about AI advancements and implementing comprehensive security strategies, businesses can effectively – and safely-navigate today’s evolving cybersecurity landscape.  Contact us today to learn more about how our AI technologies can help protect your business from the ever-growing threat of AI being used against you by cybercriminals.

About Technical Support International

TSI is 35-year old cybersecurity (MSSP) and IT support (MSP) company specializing in helping DIB organizations address their NIST 800-171 and CMMC compliance obligations. As a CMMC-AB Registered Provider Organization (RPO), TSI offers a complete NIST 800-171 and CMMC support solution to help guide our clients toward a successful certification audit and provide the assurance that they’re adhering to these expansive compliance requirements.