Attacks on AI
Prompt injection: attacks on the AI tools you use
Prompt injection tricks an AI tool into following instructions hidden in the content it reads. The NCSC doubts it can ever be removed entirely, so the focus is on limiting what a manipulated tool can do.
Last reviewed against NCSC (UK), UK Government (DSIT and Home Office) and Anthropic. Sources
The idea
Data that behaves like instructions
The NCSC describes prompt injection as an attack where crafted input makes a model act unexpectedly, such as leaking confidential information or triggering effects in systems that accept unchecked input [9]. It calls it one of the most widely reported weaknesses in large language models [9]. It is also a form of social engineering aimed at a machine: the attacker persuades the tool, not a person.
Why it is different
Not like SQL injection
In a December 2025 blog, the NCSC's Dave Chismon argued that prompt injection should not be treated as a form of SQL injection [2]. SQL injection can be fixed with parameterised queries, but language models lack a clear boundary between instructions and data, and the NCSC described them as inherently confusable [2]. The aim should be to reduce the likelihood and impact of attacks, not expect a complete fix [2].
What the NCSC suggests
Four lines of defence
Awareness
Developers need to recognise it as a class of vulnerability, and security teams should accept that some risk always remains whatever product is bought [2].
Secure design
Rely on safeguards that do not depend on the model, and reduce the privileges of a model that processes untrusted input [2].
Make it harder
Separate data from instructions where possible, and be wary of deny-list filters, because attackers can rephrase around them [2].
Monitor
Log inputs, outputs and tool or API calls, and watch for failed calls that may signal an attack in progress [2].
Prevalence
What the surveys say
Gartner's survey found 32% of respondents said attackers had used prompt injection against their applications [7]. The article does not give the sample size [7].
Ask your suppliers
For each AI product you use, ask what it can read, what actions it can take on your behalf and what logs exist. The NCSC says the burden of using AI safely should not fall on individual users [9].
Keep reading
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Outlook
What the NCSC expects from AI-enabled cyber threats to 2027, including volume, speed of exploitation and the gap between organisations that keep pace.
Read the guideHow CyPro can help
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