Artificial intelligence (“AI”) systems are indeed powerful – but they are not perfect.  There are numerous reports of “hallucinations” where the systems simply make up content.  Now, a respected research group, the Open Worldwide Application Security Group, has issued a comprehensive report on prime cybersecurity vulnerabilities of AI systems and large language models on which they're based.

We'll focus this article on malicious prompt injection attacks.  These can manipulate a large language model (LLM) through crafty inputs, causing unintended actions by the LLM. Direct injections overwrite system prompts, while indirect ones manipulate inputs from external sources.

Summary:

1. Prompt injection attacks manipulate AI by embedding malicious instructions.
2. They can lead to unauthorized actions, data breaches and misinformation.
3. Securing AI against these attacks is crucial for safe applications.

Crowley Law has a great deal of experience in helping its clients recognize and deal with the risks and liabilities of technology design and implementation.  We can also help clients find ways to minimize or eliminate those risks and liabilities.  If you have a technology system you are seeking to use or market, contact us at (844) 256-5891 or [email protected] to arrange for a complimentary conversation with a member of our team.  We're here to help.

AI systems respond to user inputs, or "prompts." Attackers exploit this. They craft prompts to trigger unintended AI behavior. This vulnerability is concerning.

Short, malicious inputs can redirect AI tasks. They alter AI responses subtly or drastically. Recognizing these inputs is challenging. AI's complexity adds to this difficulty.

Attackers aim for several outcomes. They may seek sensitive information. Or, they aim to spread false information. Sometimes, their goal is system disruption. Each outcome harms trust in AI systems.

Defending against prompt injections is multifaceted. First, AI models need robust design. They should resist misleading inputs. This requires advanced programming and testing.

Second, input validation is essential. Systems must scrutinize prompts for suspicious patterns. This step reduces the risk of malicious prompt execution.

Third, user education plays a role. Users should recognize and avoid sharing sensitive information. They must understand the importance of secure prompt crafting.

Finally, ongoing monitoring is vital. Systems should log and analyze AI interactions. Anomalies indicate potential attacks. Swift detection enables quick response.

In conclusion, prompt injection attacks are a serious threat to AI systems. They exploit the way AI processes user inputs. The outcomes range from data breaches to misinformation. Defending against these attacks requires a combination of robust AI design, input validation, user education and continuous monitoring. Awareness and proactive measures are key to securing AI applications.

If you have concerns about potential liabilities in this area, contact us at (844) 256-5891 or at [email protected]  We're here to help.