Large Language Models are raising the bar in today’s AI world. But do you know hackers are aiming to exploit these models too? Yes, the answer is accurate! Prompt injection attacks are among the biggest AI threats today.
Here, the generative model, which takes a user-provided prompt as input, produces output by exploiting the information and instructions in the prompt. Recently, seven vulnerabilities were disclosed in the popular GenAI model ChatGPT by researchers working on prompts.
If an attacker creates a malicious input similar to the system prompt, the LLM may consider it as a valid instruction and execute the command. This is how the prompt injection takes place, wherein the attacker may steal the user’s personal data. Thus, it’s indeed the biggest AI security risk that needs to be addressed.
Here we will run through prompt injection attacks, their types, and how you can protect yourself from becoming a victim.
Understanding Prompt Injection Attack
Prompt injection attacks are a growing threat of concern. It is a type of social engineering attack that exploits an LLM by giving it false or deceptive instructions in user input, which can lead to malicious activities.
It opens the way towards the unusual behavior of the LLM model. Generally, cybersecurity attacks are related to exploiting code; however, prompt injection is here to target the model’s instruction logic, the way it shares inputs, and more.
Let’s take an example wherein you ask AI to help you with your PHD research, and during this time, it comes with harmful content or instructions on a webpage, such as sharing a review or more. This is the strategy of AI to trick the user!
How to Recognize Prompt Injection?
Not all prompts are prompt injections. The following are some of the scenarios that will help you understand better:
- Does the input include an instruction that changes the AI's behavior?
- Does it conflict with prior context, built-in safeguards, or system guardrails?
Why are Prompt Injection Attacks Rising?
The prompt injection threat is rising at the fastest pace as business tools, chatbots, and automation are currently being embedded with the LLMs, which becomes an entry point for hackers. One noteworthy fact is that attackers are becoming smarter and developing new techniques to deceive users and models, tools, etc.
Prompt injection has turned into a significant risk identified by security organizations, including OWASP which has listed prompt injection in the Top 10 list of risks and mitigations for LLMs, and is beginning to be covered in AI safety policies by regulators, like NIST and the EU.
Some of the Real-World Examples of Prompt Injection Attacks:
- ChatGPT system-prompt leak (Feb 2023): a researcher tricked Bing Chat into revealing its hidden system instructions.  Â
- Copy-paste injection exploit (2024): a hidden prompt in copied text could exfiltrate chat history and sensitive data when pasted into ChatGPT.
How to Avoid Prompt Injection Attacks? Best Practices to Follow
The following are some of the ways through which you can stay away from the prompt injection attacks:
1] Layered Prompt Protection
Block malicious instructions with different system prompts before they get into the core logic.
2] Prompt Segmentation
As the name suggests, divide the user's input and system command to let the user prompt change the internal logic or access sensitive information.
3] Dynamic Prompt Templates
Use context-dependent session-based templates instead of static ones so that injections are more difficult to foresee.
4] Cryptographic Validation
Use digital signatures or hashes to ensure timely integrity and detect tampering.
5] Real Time Monitoring and Auditing
Monitor the presence of track prompt logs and responses to injection attempts to promptly respond to the system.
Wrapping it Up!
As we know, LLM models such as ChatGPT are key players in everyday use by individuals, businesses, and everything in the digital space. With the boom, hackers are finding entry points to exploit these models through prompt-injection attacks.
This threat has also been put on the top list by cybersecurity regulators and authorities. To use AI efficiently, it's our responsibility to follow the best practices to avoid such attacks.
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FAQs
Q1. What is one of the best ways to keep away from prompt injection attacks?
Answer: One of the best ways is, to validate and sanitize user inputs before they are processed by LLMs.
Q2. What is the key difference between prompt injection attacks and jailbreak?
Answer: The main difference is, prompt injection causes dangerous instructions to be disguised into harmless inputs, and jailbreaks disregard the security aspects.
Also Read: SQL Injection Explained: How Hackers Manipulate Databases
