As artificial intelligence (AI) continues to expand across Government operations, Federal agencies must integrate advanced AI technology to strengthen cybersecurity while staying ahead of new cyber threats. This is especially crucial in environments where critical systems, personally identifiable information (PII), and critical infrastructure are constantly targeted by sophisticated adversaries.
AI is a double-edged sword. Malicious actors now use machine learning techniques, deep learning and generative AI to scale cyberattacks at unprecedented speed. At the same time, security teams are successfully deploying advanced AI algorithms, security tools and threat intelligence to detect, defend and respond faster. Striking the right balance is essential for Federal leaders responsible for safeguarding national interests.
In this article, we’ll talk about how to find the right balance between exploiting AI’s capabilities and guarding against the risks. We’ll also explore the specific threats agencies face today, and discuss how AI can help by automating risk management.
The Growing Cybersecurity Challenge
Ransomware, large-scale phishing campaigns and deepfake social engineering attacks are accelerating due to advancements in AI systems and large language models (LLMs). Cybercriminals can cast a wider net than ever before, with little effort and at a low cost to themselves, especially when targeting critical infrastructure and Federal systems.
It’s worth noting that even benign AI applications are paving the way for more cyber events. When Government agencies adopt AI tools, they automatically expand their networks and their “attack surfaces,” requiring new security measures and stronger vulnerability assessment practices.
AI’s automation and speed enable large-scale attacks. AI can rapidly scan and scrape online databases and analyze network traffic, looking for potential targets to attack. Hackers can use AI’s no-code automation capabilities to create the code for malware at high speed, and to send out phishing emails at a larger scale than ever before. AI’s natural language processing (NLP) capabilities allow it to create credible “deepfake” video and audio at high speed, as well.
The vast majority of these attacks are unsuccessful, but it only takes one careless end user to click a bad link to a malicious website, or to click a link that triggers a domain blocking failure. That’s why it’s so important for security teams to be on their guard. Fortunately, AI tools can also help. Just as no-code automation helps hackers, it also helps agencies protect themselves against threats.
Leveraging AI Tools To Fight Cyberattacks
The same capabilities that can make AI useful for hackers also make it a great tool in fighting cyber threats. Automation, speed and the ability to identify patterns are all invaluable for countering online threats.
Using AI to Identify Phishing Attacks
AI excels at assisting with phishing detection. AI and Machine Learning (ML) tools can quickly “read” incoming emails and texts and scan them for telltale signs of danger, like unusual sender addresses. AI’s natural language processing capabilities also help. NLP tools scan incoming messages for unusual phrasing or a strange tone, which might indicate a phishing attack.
Most spam folders are powered by AI and ML tools. These tools are constantly learning on the job, too. Whenever you mark an incoming email “spam,” your software learns a little more about what you consider to be spam. Going forward, it incorporates that information into its workflow.
AI-powered antivirus tools scan for malware more effectively than older antivirus detection systems. The AI software scans and analyzes huge quantities of data in network traffic and system logs to identify patterns that could indicate a virus. Because deep learning models are so good at identifying patterns and spotting anomalies, it can often spot new viruses early on.
Older antivirus software relies on known viral signatures. While useful, these tools can’t keep up with new threats evolving through AI algorithms. That’s the AI difference: predictive pattern detection supports proactive cybersecurity solutions and strengthens incident response.
Using AI To Identify Threats From Within
AI can help to spot attacks from within. The software establishes a baseline of user behavior, like normal login hours and normal patterns of data access. When there’s a change in that baseline, the AI tool flags it for further investigation.
AI looks for changes like unusual activity outside of a team member’s normal working hours or location-based aberrations. For example, if a member of your team normally logs in at 9 a.m. and out at 5 p.m., the AI tool will notice if they start logging in again at midnight to download files. Even if they have authorization to view that information, it’s worth asking why they suddenly need to access it at an unusual time. In the same vein, further review may be warranted if an employee views a record from an atypical IP address.
Using AI To Actively Fight Threats
Beyond identifying cyber threats, AI tools can proactively defend systems. They block or isolate compromised devices, enforce malicious domain blocking, apply system patches and notify security teams of attempted attacks.
AI-backed incident response workflows reduce the spread of malware and help protect the network even when one endpoint is compromised.
Exercising Precaution: Building Guardrails for AI
AI is a valuable tool for fighting cyber threats. However, it’s important to protect your network and end users against AI’s natural pitfalls. Federal agencies have a special responsibility to install guardrails in accordance with the relevant regulations and guidelines.
AI guardrails ensure that the technology behaves according to ethical standards, avoiding bias and making appropriate use of sensitive data. To some extent, AI itself can create guidelines. Generative AI tools can routinely scan for ethical problems and alert managers to any new issues.
However, human oversight remains crucial, and agencies should appoint managers to be directly accountable for AI supervision. The NIST AI Risk Management Framework provides detailed guidance for managers and anyone else involved in managing AI guardrails.
Making the Best Use of AI
Government agencies can’t turn their backs on AI. The technology offers too many benefits to stop using it. However, leaders must be aware that expanding AI also opens them up to greater threats. It’s also critical to be alert to the many dangers posed by AI-enabled cyberattacks.
The first step? Inform yourself about how AI can impact your agency. To get started, learn about AI integration into GRC today.
