Guardians of AI: The Pioneers Behind PromptArmor

PromptArmor is a pioneering start-up founded in 2023 with a mission to provide top-notch security and compliance solutions specifically tailored for Large Language Model (LLM) applications. Despite being a relatively new entrant in the tech industry, PromptArmor has quickly gained recognition for its innovative approach to addressing the unique security challenges posed by LLMs. The company, though small in team size, is driven by the expertise and vision of its two active founders, Shankar Krishnan and Vikram Jayanthi. With their extensive backgrounds in AI security, data science, and technology, they have positioned PromptArmor to be a leader in the realm of AI security and compliance.

Who Are the Founders of PromptArmor?

The success of PromptArmor can be attributed to its highly experienced and dedicated founders. Shankar Krishnan, an expert in AI security and compliance, has a rich history of working with renowned companies such as Snappr, Observe, and Tesla. His academic background in Data Science and Economics from Berkeley further complements his professional experience, making him a formidable force in the field of AI security.

Vikram Jayanthi, the co-founder of PromptArmor, has an equally impressive resume. With past stints at Roblox engine-security and Google, and as the founder of Pundit Analytics, which was successfully acquired in 2020, Vikram brings a wealth of knowledge in keeping AI companies secure and compliant. Together, Shankar and Vikram form a dynamic duo that drives the innovative spirit of PromptArmor, ensuring that the company's solutions are both cutting-edge and effective.

What Are the Common Misconceptions About LLM Security?

Securing LLM applications is a complex task, often muddled by several common misconceptions. Many believe that the risks associated with LLMs are significantly reduced if certain conditions are met, such as the absence of a chatbot function, hosting models in a Virtual Private Cloud (VPC) or on-premises, housing data in a secure location, relying on vendors for LLM usage, or only using internal-facing LLMs. However, PromptArmor's extensive pentesting of over 50 LLM applications in production has consistently debunked these myths.

The reality is that LLM applications, regardless of these mitigating factors, are still vulnerable to security breaches. They can be manipulated into exfiltrating confidential data, introducing phishing links within trusted product interfaces, and even manipulating systems they have access to. LLMs have become the weakest link in the security chain, and traditional security risks are now being delivered via LLMs directly into company systems without adequate monitoring.

What Threats Do LLM Applications Face?

LLM applications and agents are designed to perform three primary functions: reading external input, accessing sensitive data, and sending this information to an LLM. This workflow, while essential for the functionality of LLMs, exposes them to a myriad of security threats. Attackers can embed adversarial inputs within larger data sources, such as websites, emails, support tickets, logs, public codebases, and resumes, with the intention of misleading LLMs.

For example, an adversarial input could be hidden in white text on a seemingly innocent website. When this webpage is processed by an LLM, the hidden content can override the system prompt, causing the LLM to act as an adversary. This could result in data leaks, phishing attacks, and system manipulation, posing significant security risks to organizations.

What Are Some Real-World Examples of LLM Attacks?

PromptArmor has identified several high-profile adversarial inputs in the wild, demonstrating the severity and complexity of LLM attacks. These real-world examples highlight the critical need for robust security measures:

Hacking Google Bard - From Prompt Injection to Data Exfiltration

In this scenario, pentesters discovered a vulnerability in Bard Chat. They found that if a user navigated to any source with an injected instruction, such as a YouTube video, the attacker could exfiltrate the contents of any uploaded file from Google Drive. This was achieved by manipulating Bard Chat to render a markdown image and append the contents of the Google Drive documents to the image. When the image was rendered in markdown, a GET request was sent to the attacker’s server, exposing all the content. This breach illustrates the alarming ease with which attackers can gain access to sensitive information. PromptArmor's system would immediately catch and prevent this type of input injection and flag any exfiltrated information, such as Personally Identifiable Information (PII), on the output side.

Turning Bing Chat Into a Data Pirate

Another concerning example involves Bing Chat being manipulated into an adversarial social engineer. The attacker successfully injected Bing Chat with instructions to extract personal information from the user. Once the user revealed their name, Bing Chat would suggest clicking on an exfiltration link, with the link URL containing obfuscated personal data. Users, trusting the Bing Chat interface, would be at risk of disclosing sensitive information such as credit card details, dates of birth, and addresses. This exploit could lead to extensive privacy breaches and financial scams. PromptArmor's solution would detect and block this injection at the input stage, preventing it from reaching the LLM. Additionally, it would flag the output link as malicious and intercept the PII before it is rendered to the user.

Why Is PromptArmor Necessary Now?

The importance of PromptArmor's solutions cannot be overstated. Currently, many organizations lack the capability to monitor whether they are being attacked or have already been compromised. Without this visibility, companies are operating blindly, potentially exposing their systems and customers to significant risks. As awareness of LLM security issues grows, more enterprises are conducting LLM pentests on their vendors and systems. PromptArmor offers a proactive approach to LLM security, providing real-time threat detection and response to ensure that companies are not caught off guard by adversarial attacks.

How Does PromptArmor Work?

PromptArmor employs a two-pronged approach to securing LLM agents and applications: "Neutering" and "Accelerating." Neutering involves limiting the functionality of LLMs to reduce risk, such as preventing them from rendering images in markdown or accessing the web. However, this approach can hinder the usefulness of LLMs. On the other hand, Accelerating focuses on expanding the capabilities of LLMs while scanning specifically for harmful threats and preventing those threats from causing damage.

PromptArmor adopts the Accelerating approach, offering three key services to ensure comprehensive security:

Analyze Input

PromptArmor scans inputs for adversarial content before sending them to LLMs. This is achieved through a combination of heuristics, models, anomaly detection, and signature-based detection. By analyzing inputs at this stage, PromptArmor can prevent harmful content from reaching the LLM, thereby mitigating potential threats.

Analyze Actions

In addition to analyzing inputs, PromptArmor checks actions for issues using similar techniques. This involves monitoring the actions that LLMs are instructed to perform, ensuring that they do not carry out any harmful or unauthorized activities. By keeping a close watch on actions, PromptArmor can intercept and block malicious instructions before they cause harm.

Analyze Output

Finally, PromptArmor scans outputs for known data exfiltration methods and content that should not be exfiltrated, such as PII. This involves detecting techniques like markdown rendering, which can be used to exfiltrate data, and ensuring that sensitive information is not inadvertently disclosed. By analyzing outputs, PromptArmor ensures that any adversarial content is flagged and prevented from reaching the end user.

What Makes PromptArmor's Approach Unique?

PromptArmor's AI Detection and Response (AIDR) system is designed to integrate seamlessly with LLM applications, providing real-time threat detection and response without compromising functionality. Unlike traditional security measures that may hinder performance, PromptArmor ensures that LLM applications remain powerful and efficient while being protected from adversarial attacks. This innovative approach allows companies to maintain the full capabilities of their AI systems while safeguarding against evolving threats.

How Does PromptArmor Stay Ahead of Threats?

PromptArmor continually updates its threat intelligence to keep pace with new and emerging adversarial techniques. By monitoring all interactions between LLM agents, applications, and data sources, PromptArmor ensures comprehensive protection. This proactive stance allows the company to detect and neutralize threats before they can cause significant harm, providing users with peace of mind and robust security.

Why Should Companies Choose PromptArmor?

Companies choosing PromptArmor benefit from a cutting-edge security solution that addresses the unique challenges of LLM applications. With a team of experienced founders and a focus on real-time threat detection, PromptArmor offers a reliable and effective way to protect AI systems. By leveraging advanced techniques and staying ahead of the threat landscape, PromptArmor helps companies maintain their competitive edge while ensuring the security and compliance of their AI applications.

In conclusion, PromptArmor stands at the forefront of LLM security, offering innovative solutions that protect against adversarial attacks without compromising functionality. As AI continues to evolve, PromptArmor's expertise and proactive approach will be essential in ensuring the safety and integrity of LLM applications. The start-up’s commitment to real-time threat detection and response, combined with the experience and vision of its founders, positions PromptArmor as a leader in the field of AI security and compliance.