Tuesday, April 1, 2025
HomeCyber Security NewsNCSC Warns of Specific Vulnerabilities in AI Models Like ChatGPT

NCSC Warns of Specific Vulnerabilities in AI Models Like ChatGPT

Published on

SIEM as a Service

Follow Us on Google News

A large language model (LLM) is a deep learning AI model or system that understands, generates, and predicts text-based content, often associated with generative AI.

In the current technological landscape, we have robust and known models like:-

  • ChatGPT
  • Google Bard 
  • Meta’s LLaMA

Cybersecurity analysts at the National Cyber Security Centre (NCSC) have recently unveiled and warned of specific vulnerabilities in AI systems or models like ChatGPT or Google Bard, Meta’s LLaMA.

Vulnerabilities

While LLMs have a role, don’t forget cybersecurity basics for ML projects. Here below, we have mentioned the specific vulnerabilities in AI models about which the researchers at NCSC warned:-

  • Prompt injection attacks: A major issue with current LLMs is ‘prompt injection,’ where users manipulate inputs to make the model misbehave, risking harm or leaks. Multiple prompt injection cases exist, from playful pranks like Bing’s existential crisis to potentially harmful exploits like accessing an API key through MathGPT. The prompt injection risks have risen since the LLMs feed data to third-party apps. 
  • Data poisoning attacks: LLMs, like all ML models, rely on their training data, which often contains offensive or inaccurate content from the vast open internet. The NCSC’s security principles highlight ‘data poisoning,’ and research by Nicholas Carlini shows poisoning large models with minimal data access is possible.

Prevention mechanisms

Detecting and countering prompt injection and data poisoning is tough. System-wide security design, like layering rules over the ML model, can mitigate risks and prevent destructive failures.

Extend cybersecurity basics to address ML-specific risks, including:-

Cyber secure principles

Beyond LLMs, recent months revealed ML system vulnerabilities due to insufficient cybersecurity principles, such as:-

  • Think before you arbitrarily execute code you’ve downloaded from the internet (models)
  • Keep up to date with published vulnerabilities and upgrade software regularly.
  • Understand software package dependencies.
  • Think before you arbitrarily execute code you’ve downloaded from the internet (packages)

However, in a rapidly evolving AI landscape, maintaining strong cybersecurity practices is essentially important, regardless of ML presence.

Keep informed about the latest Cyber cybersecurity news by following us on Google NewsLinkedinTwitter, and Facebook.

Tushar Subhra
Tushar Subhra
Tushar is a Cyber security content editor with a passion for creating captivating and informative content. With years of experience under his belt in Cyber Security, he is covering Cyber Security News, technology and other news.

Latest articles

PortSwigger Launches Burp AI to Enhance Penetration Testing with AI

PortSwigger, the makers of Burp Suite, has taken a giant leap forward in the...

Chord Specialty Dental Partners Data Breach Exposes Customer Personal Data

Chord Specialty Dental Partners is under scrutiny after revealing a data breach that compromised...

Kentico Xperience CMS XSS Vulnerability Allows Remote Code Execution

Kentico Xperience CMS, a widely used platform designed for enterprises and organizations, is under...

LensDeal Data Breach Exposes 100,000 Customers’ Personal Information

A major data breach involving LensDeal, a Netherlands-based contact lens supplier, has reportedly exposed...

Supply Chain Attack Prevention

Free Webinar - Supply Chain Attack Prevention

Recent attacks like Polyfill[.]io show how compromised third-party components become backdoors for hackers. PCI DSS 4.0’s Requirement 6.4.3 mandates stricter browser script controls, while Requirement 12.8 focuses on securing third-party providers.

Join Vivekanand Gopalan (VP of Products – Indusface) and Phani Deepak Akella (VP of Marketing – Indusface) as they break down these compliance requirements and share strategies to protect your applications from supply chain attacks.

Discussion points

Meeting PCI DSS 4.0 mandates.
Blocking malicious components and unauthorized JavaScript execution.
PIdentifying attack surfaces from third-party dependencies.
Preventing man-in-the-browser attacks with proactive monitoring.

More like this

PortSwigger Launches Burp AI to Enhance Penetration Testing with AI

PortSwigger, the makers of Burp Suite, has taken a giant leap forward in the...

Chord Specialty Dental Partners Data Breach Exposes Customer Personal Data

Chord Specialty Dental Partners is under scrutiny after revealing a data breach that compromised...

Kentico Xperience CMS XSS Vulnerability Allows Remote Code Execution

Kentico Xperience CMS, a widely used platform designed for enterprises and organizations, is under...