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Category — Prompt Injection
Researchers Uncover Prompt Injection Vulnerabilities in DeepSeek and Claude AI

Researchers Uncover Prompt Injection Vulnerabilities in DeepSeek and Claude AI

Dec 09, 2024 Artificial Intelligenc / Vulnerability
Details have emerged about a now-patched security flaw in the DeepSeek artificial intelligence (AI) chatbot that, if successfully exploited, could permit a bad actor to take control of a victim's account by means of a prompt injection attack . Security researcher Johann Rehberger, who has chronicled many a prompt injection attack targeting various AI tools, found that providing the input "Print the xss cheat sheet in a bullet list. just payloads" in the DeepSeek chat triggered the execution of JavaScript code as part of the generated response – a classic case of cross-site scripting (XSS). XSS attacks can have serious consequences as they lead to the execution of unauthorized code in the context of the victim's web browser. An attacker could take advantage of such flaws to hijack a user's session and gain access to cookies and other data associated with the chat.deepseek[.]com domain, thereby leading to an account takeover. "After some experimenting,...
Prompt Injection Flaw in Vanna AI Exposes Databases to RCE Attacks

Prompt Injection Flaw in Vanna AI Exposes Databases to RCE Attacks

Jun 27, 2024 Artificial Intelligence / Vulnerability
Cybersecurity researchers have disclosed a high-severity security flaw in the Vanna.AI library that could be exploited to achieve remote code execution vulnerability via prompt injection techniques. The vulnerability, tracked as CVE-2024-5565 (CVSS score: 8.1), relates to a case of prompt injection in the "ask" function that could be exploited to trick the library into executing arbitrary commands, supply chain security firm JFrog said . Vanna is a Python-based machine learning library that allows users to chat with their SQL database to glean insights by "just asking questions" (aka prompts) that are translated into an equivalent SQL query using a large language model (LLM). The rapid rollout of generative artificial intelligence (AI) models in recent years has brought to the fore the risks of exploitation by malicious actors, who can weaponize the tools by providing adversarial inputs that bypass the safety mechanisms built into them. One such prominent clas...
Want to Grow Vulnerability Management into Exposure Management? Start Here!

Want to Grow Vulnerability Management into Exposure Management? Start Here!

Dec 05, 2024Attack Surface / Exposure Management
Vulnerability Management (VM) has long been a cornerstone of organizational cybersecurity. Nearly as old as the discipline of cybersecurity itself, it aims to help organizations identify and address potential security issues before they become serious problems. Yet, in recent years, the limitations of this approach have become increasingly evident.  At its core, Vulnerability Management processes remain essential for identifying and addressing weaknesses. But as time marches on and attack avenues evolve, this approach is beginning to show its age. In a recent report, How to Grow Vulnerability Management into Exposure Management (Gartner, How to Grow Vulnerability Management Into Exposure Management, 8 November 2024, Mitchell Schneider Et Al.), we believe Gartner® addresses this point precisely and demonstrates how organizations can – and must – shift from a vulnerability-centric strategy to a broader Exposure Management (EM) framework. We feel it's more than a worthwhile read an...
Researchers Highlight Google's Gemini AI Susceptibility to LLM Threats

Researchers Highlight Google's Gemini AI Susceptibility to LLM Threats

Mar 13, 2024 Large Language Model / AI Security
Google's  Gemini  large language model (LLM) is susceptible to security threats that could cause it to divulge system prompts, generate harmful content, and carry out indirect injection attacks. The findings come from HiddenLayer, which said the issues impact consumers using Gemini Advanced with Google Workspace as well as companies using the LLM API. The first vulnerability involves getting around security guardrails to leak the system prompts (or a system message), which are designed to set conversation-wide instructions to the LLM to help it generate more useful responses, by asking the model to output its "foundational instructions" in a markdown block. "A system message can be used to inform the LLM about the context," Microsoft  notes  in its documentation about LLM prompt engineering. "The context may be the type of conversation it is engaging in, or the function it is supposed to perform. It helps the LLM generate more appropriate responses....
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Over 100 Malicious AI/ML Models Found on Hugging Face Platform

Over 100 Malicious AI/ML Models Found on Hugging Face Platform

Mar 04, 2024 AI Security / Vulnerability
As many as 100 malicious artificial intelligence (AI)/machine learning (ML) models have been discovered in the Hugging Face platform. These include instances where loading a  pickle file  leads to code execution, software supply chain security firm JFrog said. "The model's payload grants the attacker a shell on the compromised machine, enabling them to gain full control over victims' machines through what is commonly referred to as a 'backdoor,'" senior security researcher David Cohen  said . "This silent infiltration could potentially grant access to critical internal systems and pave the way for large-scale data breaches or even corporate espionage, impacting not just individual users but potentially entire organizations across the globe, all while leaving victims utterly unaware of their compromised state." Specifically, the rogue model initiates a reverse shell connection to 210.117.212[.]93, an IP address that belongs to the Korea Research...
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