By Brijesh Balakrishnan, VP & Global Head – Cybersecurity, Infosys
The cybersecurity landscape is undergoing a fundamental transformation as artificial intelligence emerges as both the ultimate weapon and the essential shield in digital warfare. Organisations worldwide find themselves caught in an escalating arms race where the same technology that promises to revolutionise cyber defense is simultaneously empowering attackers with unprecedented capabilities. The other aspect is the numerous vulnerabilities of generative and agentic AI systems themselves, like prompt injection, model poisoning etc which can be exploited by attackers. This trinity defines the modern security paradigm, where success hinges not just on adopting AI, but on wielding it more effectively and securely than adversaries.
The Expanding Battlefield
Today’s attack surfaces have grown exponentially beyond traditional network perimeters. Cloud infrastructure, IoT devices, remote workforces, and interconnected supply chains create a vast ecosystem of potential vulnerabilities. Each endpoint represents a possible entry point for malicious actors, making comprehensive security coverage increasingly complex and resource-intensive.
Traditional reactive security models, which respond to threats after they’ve been detected, are proving inadequate against this expanding landscape. Organisations must shift toward continuous threat exposure management, constantly monitoring, assessing, and mitigating risks across their entire digital footprint. This proactive approach requires real-time visibility into potential vulnerabilities and the ability to quantify risks with precision, enabling security teams to prioritise their efforts where they matter most.
The Agentic AI Security Challenge
The emergence of agentic AI systems – autonomous agents capable of making independent decisions and taking actions – introduces new layers of complexity to the cybersecurity equation. These systems present unique risks that traditional security frameworks struggle to address.
- Autonomous Decision-Making Risks: Agentic AI systems can make decisions without human oversight, potentially leading to unintended consequences or exploitation by malicious actors. If compromised, these agents could make decisions that appear legitimate while serving adversarial purposes.
- Data Poisoning and Model Manipulation: Attackers can potentially compromise agentic AI systems by feeding them malicious training data or manipulating their decision-making processes. This could result in agents that appear to function normally while systematically undermining security protocols.
- Privilege Escalation Concerns: Agentic AI systems often require elevated permissions to perform their functions effectively. If compromised, these elevated privileges could provide attackers with extensive access to organisational systems and data.
AI as the Great Equaliser in Cyber Defense
Generative AI and agentic AI is revolutionising defensive cybersecurity capabilities by processing and analysing threat data at unprecedented scale and speed. Machine learning algorithms can sift through millions of security events, identifying patterns and anomalies that would overwhelm human analysts. This enhanced threat detection capability allows security teams to spot sophisticated attacks that might otherwise go unnoticed.
AI-powered security systems excel at correlating seemingly unrelated events across multiple data sources, creating comprehensive threat pictures that enable faster, more informed responses. These systems can automatically update threat signatures, adapt to new attack vectors, and even predict potential security incidents before they occur. The agility afforded by AI-driven defense mechanisms allows organisations to stay ahead of rapidly evolving threats.
Furthermore, AI democratises advanced cybersecurity capabilities, enabling smaller organisations to deploy enterprise-grade security measures without massive human resources. Automated threat hunting, intelligent incident response, and predictive risk assessment become accessible to organisations of all sises, leveling the playing field against well-resourced adversaries.
The Dark Side: AI-Enabled Cyber Attacks
However, the same technological advances that strengthen defenses are simultaneously amplifying offensive capabilities. Attackers are leveraging generative AI to craft more sophisticated and evasive threats that can adapt and evolve in real-time. AI-generated phishing emails are becoming increasingly convincing, incorporating personalised details scraped from social media and public databases to bypass traditional detection methods.
Advanced persistent threat actors are using machine learning to study network behaviors, identifying optimal timing and methods for infiltration. AI-powered malware can morph its signature to evade detection systems, while deepfake technology enables more convincing social engineering attacks. The automation of attack processes allows smaller criminal organisations to launch sophisticated campaigns previously reserved for nation-state actors.
Perhaps most concerning is the potential for AI to accelerate vulnerability discovery and exploitation. Automated systems can scan for sero-day vulnerabilities across vast codebases, potentially identifying and weaponising security flaws faster than defenders can patch them.
The Path Forward
Organisations deploying agentic AI systems must implement comprehensive security frameworks that include continuous behavioral monitoring to detect deviations from expected operations, sandboxing environments with clearly defined boundaries and access limitations, multi-factor authentication requiring validation steps or human approval for critical decisions, regular model validation and red team testing to ensure systems haven’t been compromised through data poisoning or manipulation, and sero-trust architecture principles that require continuous identity and authorisation verification for each action. These layered security measures work together to mitigate the unique risks posed by autonomous AI agents while reducing the potential impact of system compromises.
The battle for cybersecurity supremacy will be won by organisations that effectively harness AI’s defensive capabilities while mitigating its risks through continuous investment in AI-driven security technologies, comprehensive risk frameworks, and robust governance structures. Success requires shifting from static security controls to adaptive processes, prioritising security awareness and training to ensure effective human-AI collaboration with appropriate oversight. The future lies not in choosing between human expertise and artificial intelligence, but in creating synergistic partnerships that leverage both strengths to master the evolving digital battlefield.