By Mackenzie Gryder
This blog is part of Gate 15’s blog series “Riding the Tiger: AI Threats and Opportunities”, highlighting the essential considerations for organizational leaders and security professionals.
Introduction
Welcome to Gate 15’s blog series “Riding the Tiger: Artificial Intelligence (AI) Threats and Opportunities”, highlighting essential AI security considerations for organizational leaders and security professionals. Every week, we’ll be sharing insights, best practices, and actionable strategies to help your organization responsibly leverage AI while safeguarding data, operations, and reputation. Each post in the series will examine a different aspect of AI adoption, threat mitigation, and resilience, while providing actionable insights to help organizations navigate evolving AI risks and harness the technology effectively.
Introduction
Artificial intelligence is rapidly reshaping the cybersecurity landscape not only on the defensive side, but also in how adversaries plan, test, and execute operations. While organizations are investing in AI to enhance detection, response, and resilience, adversaries are leveraging the same technologies to scale, automate, and refine their attack methods.
Red teams, penetration testers, and real-world threat actors are already integrating AI into their workflows to increase efficiency, evade detection, and exploit both technical and human vulnerabilities. The result is a more adaptive and persistent threat environment, where attackers are faster, more personalized, and harder to distinguish from legitimate activity.
The Shift Toward AI-Enabled Offensive Operations
Traditional cyber operations often require significant time, expertise, and manual effort. AI is changing that dynamic by lowering barriers to entry while simultaneously enhancing the capabilities of more advanced actors.
- Automation of reconnaissance and vulnerability discovery
- Rapid generation of tailored phishing and social engineering content
- Real-time adaption of attack strategies based on target responses
- Scaling of attacks across multiple targets with minimal human input
For red teams, this means more realistic simulations that better reflect modern threats. For adversaries, it means increased speed and scale, allowing campaigns to evolve in near real time.
AI in Reconnaissance and Targeting
Attackers can now use AI to:
- Aggregate and analyze large volumes of open-source intelligence (OSINT)
- Identify organizational structures, key personnel, and digital footprints
- Map relationships between individuals and systems
- Prioritize high-value targets based on behavioral and contextual data
Machine learning models can process social media, public records, and leaked data sets far faster than human analysts, producing detailed targeting profiles in minutes. This allows attackers to craft highly specific campaigns that increase the likelihood of success. Red teams are similarly using AI to simulate adversary reconnaissance, helping organizations understand what information is exposed and how it could be weaponized.
Advanced Social Engineering and Phishing
Large language models can generate:
- Convincing emails that mimic tone, grammar, and organizational language
- Context-aware messages tailored to specific roles or individuals
- Multilingual communications with near-native fluency
- Iterative variations to bypass spam filters and detection tools
In addition, AI-generated voice cloning and deepfake technology are being used to impersonate executives or trusted contacts in real time. These attacks can be used to authorize fraudulent transactions, request sensitive information, or manipulate employees during high-pressure situations.
Living Off the Land with AI Assistance
Rather than relying solely on malware, attackers are increasingly adopting “living off the land” techniques using legitimate tools and administrative functions to achieve their objectives. AI enhances this approach by:
- Identifying which tools and processes are commonly used within a target environment
- Recommending attack paths that blend in with normal activity
- Automating command generation for native system utilities
- Reducing the need for custom exploit development
By leveraging trusted tools, attackers can avoid triggering traditional security controls that focus on known malicious signatures. AI further refines this process by learning from defensive responses and adjusting tactics accordingly.
AI-Driven Vulnerability Discovery and Exploitation
Capabilities include:
- Automated code analysis to identify security flaws
- Generating proof-of-concept exploits based on identified weaknesses
- Recommending exploitation strategies based on system configurations
While these techniques are also used defensively, adversaries can leverage them to shorten the time between vulnerability disclosure and active exploitation. In some cases, AI may enable the discovery of previously unknown vulnerabilities, increasing the risk of zero-day attacks. Red teams are adopting similar tools to test organizational resilience against rapidly evolving exploit scenarios.
Evasion and Adaptive Attack Behavior
- Modify payloads to evade signature-based detection
- Adjust timing and behavior to avoid anomaly detection systems
- Test multiple attack vectors simultaneously and select the most effective
- Learn from failed attempts to improve future success rates
This creates a feedback loop where attacks become progressively more sophisticated over time. Defense systems that rely on static rules or known indicators may struggle to keep pace with this level of adaptability.
The Red Team Perspective
Red teams are leading the adoption of offensive AI to better emulate real-world threats. Current use cases include generating realistic phishing campaigns, simulating insider threats, automating lateral movement, and testing detection against AI-modified attack patterns. These exercises help organizations identify gaps in both technology and processes.
A Rapidly Evolving Threat Landscape
Offensive AI is already shaping modern attacks, increasing their speed, scale, and sophistication. While this creates new challenges, it also presents an opportunity for organizations to strengthen resilience using the same technologies. AI’s impact ultimately depends on how it is applied.
Building on this threat overview, the next post in this series is “AI in Cybersecurity Defense: Best Practices and Limitations,” which will take a closer look at how artificial intelligence can be applied to enhance physical security and emergency response capabilities.
Gate 15 works across Critical Infrastructure sectors to help organizations protect their people, places, data, and dollars. The threat environment is constantly shifting, and we are here to boost your resilience with plans, exercises, threat analysis, and operational support against both emerging and enduring threats. Contact our team at Gate15@gate15.global to see how we can assist you in delivering on your mission. Join Gate 15’s Resilience and Intelligence Portal (the GRIP)! Sign up today to stay informed of what’s new in all-hazards homeland security and join us in securing America’s people, places, data, and dollars.
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