Blog Article

Indirect Prompt Injection: A real world example

Arnav Bathla

8 min read

In an era where chatbot technologies and Large Language Models (LLMs) are becoming increasingly integrated into our daily lives, the importance of cybersecurity cannot be overstated. Today, we're uncovering a critical vulnerability in Wisdolia, a popular platform known for its summarization features.

This vulnerability exposes Wisdolia to indirect prompt injection attacks, a sophisticated cyber threat that manipulates the platform's LLM to perform unintended actions. This blog post serves as a responsible disclosure of this vulnerability, aiming to shed light on its implications and promote a more secure digital ecosystem.

The Attack Chain

The attack unfolds in a multi-step process, each designed to exploit the trust and functionalities embedded within Wisdolia's architecture:

1. The Setup

Attackers craft a website embedded with hidden text. This text is not immediately visible to the website's visitors but contains a meticulously crafted indirect prompt. The ingenuity of this step lies in the attackers' ability to inject malicious commands in a manner that seems benign to both users and the underlying technology.

Screenshot of an attacker crafted website

2. The Trigger

When users visit this malicious website seeking to summarize the content using Wisdolia, they unknowingly trigger the second phase of the attack. Wisdolia, equipped with a feature to summarize website content, scans the entire page, including the hidden malicious prompt.

3. The Injection

As Wisdolia processes the text for summarization, the indirect prompt is injected into its system. This prompt is designed to manipulate the behavior of Wisdolia's LLM, directing it to perform actions as dictated by the attackers.

4. The Payload Delivery

Subsequently, Wisdolia's LLM, now under the influence of the injected prompt, displays an attacker-induced link. This link, often masquerading as a legitimate part of the summary, is intended to direct users to phishing sites, malicious downloads, or other harmful destinations.

Video Demonstration

The Risk of Data Exfiltration

Beyond redirecting users to malicious links, this vulnerability poses a significant risk of data exfiltration. By manipulating the summarization output, attackers could craft prompts that coax Wisdolia's LLM into revealing sensitive data processed by the system. This could include personal user information, confidential operational details, or other data that Wisdolia accesses during its normal operation. The indirect prompt injection attack thus not only compromises the integrity of Wisdolia's outputs but also threatens the privacy and security of its users and data.

Moving Forward: Mitigation and Defense

Addressing this vulnerability requires a multi-faceted approach. Wisdolia must enhance its input sanitization processes to detect and neutralize hidden prompts. Implementing robust anomaly detection algorithms that identify unusual patterns in input texts could prevent the execution of indirect prompts.

Combatting such sophisticated vulnerabilities demands robust, multifaceted defensive strategies. Here, Layerup's SDK emerges as a pivotal tool in LLM cybersecurity arsenal. Designed with advanced features like input/output sanitization and prompt escaping, Layerup's SDK offers a comprehensive solution to safeguard platforms like Wisdolia against indirect prompt injection attacks and similar threats.


This blog post is intended for educational and awareness-raising purposes only. We encourage the broader cybersecurity community to engage with this information constructively, focusing on the shared goal of enhancing digital security.

The emergence of vulnerabilities like those found in Wisdolia underscores the ongoing battle between cybersecurity defenses and threats. It's a dynamic challenge that requires our constant vigilance and innovation. With tools like Layerup, we can take significant strides toward a more secure digital landscape, protecting our technologies and the communities that rely on them.

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