Prompt Engineering Slides - Generative AI by Dataknobs

PrompPromptinjection is a security vulnerability in genai and LLMs. In this attackers manipulate the prompts used to and cause it to perform unwanted actions. In Prompt injection attacker design the input to trick the LLM into performing an unintended action.


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Prompt Injection

How Does it Impact LLMs and GenAI?

The consequences of prompt injection can be severe:

Misinformation and Hate Speech: Malicious actors can trick LLMs into generating harmful content, spreading misinformation, or promoting hate speech.

Data Breaches and Unauthorized Actions: Prompt injection could be used to steal confidential information, bypass security measures, or even force LLMs to execute malicious code.

Reputation Damage: Imagine an LLM used for customer service spewing offensive content due to a prompt injection. This could severely damage an organization's reputation.

Why is it a Problem?

LLMs are increasingly integrated with external services and APIs. This connectivity makes them more susceptible to prompt injection attacks, as attackers can manipulate the data fed to the LLM through these connections.

Defending Against Prompt Injection

Researchers are actively developing safeguards against prompt injection. Dataknobs have also build a capability Kontrols to handle prompt injection. Here are some potential solutions:

Layered Defenses: A combination of techniques like input validation, code auditing, and user training can create a more robust defense. Real-time Monitoring: Constantly monitoring LLM outputs can help detect and prevent suspicious activity.

The Future of LLM Security

Prompt injection is a wake-up call for the LLM and GenAI community. By prioritizing security measures, developers can ensure these powerful tools are used for good and not manipulated for malicious purposes.

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Prompt Engineering Slides - Generative AI by Dataknobs