15 September 2025, 07:57 PM
There are LLMs everywhere now. Chatbots, writing tools, customer support, and pretty much everywhere on the web. With great power comes great responsibility. As we prepare for the end of the year 2025, the only true security for LLMs will be protecting them from manipulation, hacking, or unforeseen behaviour. Each day, more companies use AI and machine learning for business operations, so now it is important to outline how organisations should secure their systems from bad actors. This paper offers an overview of LLM security, why you should care about it, and how you can begin to explore what it means to secure LLMs.
What is LLM Security?
The focus of LLM Security is protecting large language models against risk, abuse, or malicious behaviours. This involves safeguarding their inputs, outputs, training data, and finally the LLM’s environment. As LLMs are becoming integrated into business workflows, we will need security around everything they impact, whether that is data privacy or API access. In short, LLM Security is cybersecurity for AI language models.
Why LLM Security Matters in 2025
Businesses are quickly incorporating LLMs into their workflows. Think healthcare, finance, and marketing, which means that LLMs can now process sensitive data and make decisions. In 2025, threat actors are able to leverage an array of vulnerabilities, such as exposed servers and weak access controls, like over 1100 Ollama LLM servers that were recently exposed to the internet. On top of that, LLM security vulnerabilities can be “jailbroken” and can do malicious things or create malware packaged into images and other formats. Therefore, security is absolutely warranted, not just appreciated.
Download our Sample Penetration Testing Report to understand how vulnerabilities are reported and mitigated.
What is LLM Security?
The focus of LLM Security is protecting large language models against risk, abuse, or malicious behaviours. This involves safeguarding their inputs, outputs, training data, and finally the LLM’s environment. As LLMs are becoming integrated into business workflows, we will need security around everything they impact, whether that is data privacy or API access. In short, LLM Security is cybersecurity for AI language models.
Why LLM Security Matters in 2025
Businesses are quickly incorporating LLMs into their workflows. Think healthcare, finance, and marketing, which means that LLMs can now process sensitive data and make decisions. In 2025, threat actors are able to leverage an array of vulnerabilities, such as exposed servers and weak access controls, like over 1100 Ollama LLM servers that were recently exposed to the internet. On top of that, LLM security vulnerabilities can be “jailbroken” and can do malicious things or create malware packaged into images and other formats. Therefore, security is absolutely warranted, not just appreciated.
Download our Sample Penetration Testing Report to understand how vulnerabilities are reported and mitigated.