The global cybersecurity landscape is shifting at astonishing speed, and nowhere is that more evident than in the rise of large language models, the most prominent of which is ChatGPT. For many in the UK—citizens, businesses, policymakers, and security professionals alike—the arrival of this technology has been both thrilling and disorienting. It sits at the intersection of hope and hazard: capable of supporting some of the most sophisticated defensive operations ever attempted, yet equally capable of accelerating cybercrime in ways we are only beginning to understand.
As a member of a UK academic research committee focused on emerging technologies, I’ve watched the evolution of ChatGPT with a mix of excitement and urgency. Its ability to summarise vast quantities of information, detect patterns, translate languages, interact conversationally, and even write functional code has made it a genuinely transformative technology. But its very strengths also expose vulnerabilities—vulnerabilities that adversaries are already exploring.
This article takes a deep, forward-looking look at the applications, risks, and societal implications of ChatGPT in UK cybersecurity. And because the debate around AI can so easily become polarised, I aim to provide a balanced, evidence-based, and accessible view for general readers: what this technology can do, what it cannot do, and what Britain must do to ensure it is used to build a safer digital future.
ChatGPT’s role in cybersecurity is no longer theoretical. Across industry, public institutions, and research labs, its capabilities are already being woven into defensive strategies.
Cybersecurity analysts are routinely overwhelmed by the sheer volume of alerts, logs, and threat feeds they must review daily. ChatGPT excels at digesting large quantities of information and presenting them in clear, concise summaries.
In practice, this means:
transforming raw threat-intel feeds into structured insights
speeding up the classification of potential vulnerabilities
generating plain-English explanations for non-technical stakeholders
correlating data from multiple sources more quickly than a human team could
For companies with limited cybersecurity resources—a common challenge across the UK’s SME sector—this can be transformative.
ChatGPT is being used to:
identify insecure code patterns
accelerate code review
generate security documentation
explain vulnerabilities and patches in detail
support beginners in learning secure coding practices
While it does not replace skilled developers or penetration testers, it can significantly augment them, acting almost like a tireless digital assistant.
One of the most exciting uses is in cyber-range simulations and tabletop exercises. ChatGPT can generate:
realistic phishing emails
evolving threat narratives
multi-step attack scenarios
custom adversary profiles
This allows organisations to practise in more dynamic, immersive environments without the cost or complexity of traditional simulation tools.
During a cyber attack, clarity and speed matter. ChatGPT can:
summarise active incidents
help draft response plans
provide rapid guidance on best practices
translate technical details into language suitable for leadership teams
These capabilities enable more coordinated and informed crisis management.
Generative AI democratises capability. That includes dangerous capability. One of the most important insights we’ve learned since the release of large language models is that they significantly reduce the barrier to entry for cybercrime.
Phishing has traditionally relied on human imperfection—typos, awkward phrasing, cultural misunderstandings. ChatGPT eliminates all of that.
Criminals can now produce:
flawless, personalised phishing messages
emails tailored to the victim’s industry, position, or interests
convincing fake internal communications
multi-lingual campaigns with region-specific idioms
This is perhaps the most immediate and widely recognised risk. And it matters deeply for UK citizens, who are already inundated with scams disguised as messages from HMRC, the NHS, banks, and energy suppliers.
While ChatGPT is programmed to avoid writing harmful code, determined attackers can still exploit loopholes by asking for code fragments, obfuscation techniques, or “educational examples.”
Even partial assistance can help novice attackers assemble malware more quickly.
Social engineering relies on psychological manipulation. ChatGPT can help criminals:
mimic writing styles based on publicly available text
craft emotionally convincing narratives
maintain long, believable conversations with victims
impersonate customer-service representatives
The result is a new class of attacks that are more persistent, more tailored, and much harder for victims to identify.
Generative AI’s ability to produce coherent, persuasive, and high-volume content raises concerns for:
political misinformation
public-health disinformation
consumer scams
identity-based harassment
During election periods or national emergencies, such capabilities can be weaponised to undermine social trust.
One of the most crucial questions in the AI–cybersecurity debate is governance. The UK has been relatively proactive compared to many countries, though its approach differs noticeably from the EU’s more rigid regulatory framework.
The UK government’s AI strategy emphasises:
innovation
flexibility
sector-specific rules
non-statutory guidance
This model aims to encourage economic growth and technological leadership. However, critics argue that it may leave gaps in areas where safety risks are high.
The ICO has increasingly focused on:
transparency in AI decision-making
data-protection compliance
fairness and accountability
But ChatGPT presents new challenges, particularly around training-data use, data retention, and the risk of generating personal information that appears authoritative but is entirely false.
The NCSC has taken a pragmatic and balanced stance. It recognises generative AI’s potential for improving national defence while issuing clear warnings about misuse.
The NCSC’s guidance emphasises:
secure development
AI-enhanced defensive tooling
proactive monitoring of AI-assisted threats
improving organisational resilience
The UK's cybersecurity posture is strong, but the speed of AI development means regulation often lags behind capability.
Generative AI represents a paradox. Many of the features that make ChatGPT a powerful defender also empower attackers.
Strength: Anyone can use ChatGPT to learn the basics of cybersecurity, coding, or digital hygiene.
Weakness: Anyone can exploit it to learn hacking techniques or create convincing scams.
Strength: It can create test cases, simulate attacks, and analyse unfamiliar code.
Weakness: It can also help attackers brainstorm new forms of social engineering.
Strength: It allows defenders to process vast amounts of data instantly.
Weakness: It allows attackers to automate messaging, generate phishing content at industrial scale, and adapt rapidly.
Strength: It breaks down communication barriers across global cybersecurity teams.
Weakness: It allows attackers from anywhere in the world to produce native-quality English.
As ChatGPT becomes woven into more aspects of digital life, society must confront deeper ethical dilemmas.
Complete bans on code generation are unrealistic and counterproductive, but controls are essential:
strict filtering of obviously malicious requests
traceability of harmful prompt patterns
improved safety-alignment mechanisms
AI assistants could easily become repositories of confidential information. Without robust safeguards, the risks include:
accidental data leakage
model inversion attacks
unauthorised retention
This is one of the thorniest discussions in international security. If AI becomes a tool for cyber offence, escalation risks grow significantly.
The consensus among cybersecurity scholars is clear: AI must remain strictly defensive.
For Britain to lead responsibly in AI-enabled cybersecurity, several actions are essential.
We should expand:
AI-driven intrusion detection
automated threat analysis
digital-forensic tooling
cyber-range training environments
This will ensure that defenders remain ahead of attackers in capability.
The UK must strengthen:
transparency obligations
data-protection enforcement
cybersecurity requirements for AI developers
independent auditing frameworks
Clear standards provide clarity for innovators and safety for citizens.
Digital literacy campaigns must evolve to address:
AI-generated phishing
deepfakes
personalised scams
fraudulent customer support bots
The public cannot defend themselves from threats they do not recognise.
Cybersecurity is not a battle fought solely by government agencies. The UK needs:
closer ties between academia and industry
real-time threat-information sharing
common security standards across sectors
This collective approach will strengthen national resilience.
We must deepen our understanding of:
AI hallucinations
model-extraction vulnerabilities
adversarial prompting
long-term misuse scenarios
The next breakthroughs in cybersecurity will depend on research that goes beyond immediate commercial concerns.
ChatGPT is already reshaping cybersecurity in Britain—and the pace of change is only accelerating. While the risks are real and pressing, they are not insurmountable. With thoughtful governance, robust technical safeguards, and a commitment to public education, the UK can harness this technology’s power while limiting its downsides.
We are living through a moment of extraordinary technological transformation. ChatGPT is neither a miracle nor a menace—it is a tool. A powerful, unpredictable, astonishing tool that reflects our ambitions and amplifies our weaknesses.
The challenge before us is to shape this technology with intention—to ensure that it strengthens the security of every citizen, protects our democratic institutions, and supports a thriving digital economy. If we succeed, the UK can become a global leader not just in AI innovation, but in AI responsibility.
And that is a future truly worth striving for.
