Prompt Injection | Breaking Cybersecurity News | The Hacker News

Cybersecurity researchers have disclosed a now-patched, high-severity security flaw in Cursor, a popular artificial intelligence (AI) code editor, that could result in remote code execution. The vulnerability, tracked as CVE-2025-54135 (CVSS score: 8.6), has been addressed in version 1.3 released on July 29, 2025. It has been codenamed CurXecute by Aim Labs, which previously disclosed EchoLeak . "Cursor runs with developer‑level privileges, and when paired with an MCP server that fetches untrusted external data, that data can redirect the agent's control flow and exploit those privileges," the Aim Labs Team said in a report shared with The Hacker News. "By feeding poisoned data to the agent via MCP, an attacker can gain full remote code execution under the user privileges, and achieve any number of things, including opportunities for ransomware, data theft, AI manipulation and hallucinations, etc." In other words, the remote code execution triggered by a ...

In this article, we will provide a brief overview of Pillar Security's platform to better understand how they are tackling AI security challenges. Pillar Security is building a platform to cover the entire software development and deployment lifecycle with the goal of providing trust in AI systems. Using its holistic approach, the platform introduces new ways of detecting AI threats, beginning at pre-planning stages and going all the way through runtime. Along the way, users gain visibility into the security posture of their applications while enabling safe AI execution. Pillar is uniquely suited to the challenges inherent in AI security. Co-founder and CEO Dor Sarig comes from a cyber-offensive background, having spent a decade leading security operations for governmental and enterprise organizations. In contrast, co-founder and CTO Ziv Karlinger spent over ten years developing defensive techniques, securing against financial cybercrime and securing supply chains. Together, th...

Cybersecurity researchers have disclosed a now-patched critical security flaw in a popular vibe coding platform called Base44 that could allow unauthorized access to private applications built by its users. "The vulnerability we discovered was remarkably simple to exploit -- by providing only a non-secret 'app_id' value to undocumented registration and email verification endpoints, an attacker could have created a verified account for private applications on their platform," cloud security firm Wiz said in a report shared with The Hacker News. A net result of this issue is that it bypasses all authentication controls, including Single Sign-On (SSO) protections, granting full access to all the private applications and data contained within them. Following responsible disclosure on July 9, 2025, an official fix was rolled out by Wix, which owns Base44, within 24 hours. There is no evidence that the issue was ever maliciously exploited in the wild. While vibe codin...

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React conquered XSS? Think again. That's the reality facing JavaScript developers in 2025, where attackers have quietly evolved their injection techniques to exploit everything from prototype pollution to AI-generated code, bypassing the very frameworks designed to keep applications secure. Full 47-page guide with framework-specific defenses (PDF, free). JavaScript conquered the web, but with that victory came new battlefields. While developers embraced React, Vue, and Angular, attackers evolved their tactics, exploiting AI prompt injection, supply chain compromises, and prototype pollution in ways traditional security measures can't catch. A Wake-up Call: The Polyfill.io Attack In June 2024, a single JavaScript injection attack compromised over 100,000 websites in the biggest JavaScript injection attack of the year. The Polyfill.io supply chain attack , where a Chinese company acquired a trusted JavaScript library and weaponized it to inject malicious code, affected major pl...

Cybersecurity researchers are calling attention to a new jailbreaking method called Echo Chamber that could be leveraged to trick popular large language models (LLMs) into generating undesirable responses, irrespective of the safeguards put in place. "Unlike traditional jailbreaks that rely on adversarial phrasing or character obfuscation, Echo Chamber weaponizes indirect references, semantic steering, and multi-step inference," NeuralTrust researcher Ahmad Alobaid said in a report shared with The Hacker News. "The result is a subtle yet powerful manipulation of the model's internal state, gradually leading it to produce policy-violating responses." While LLMs have steadily incorporated various guardrails to combat prompt injections and jailbreaks , the latest research shows that there exist techniques that can yield high success rates with little to no technical expertise. It also serves to highlight a persistent challenge associated with developing eth...

Google has revealed the various safety measures that are being incorporated into its generative artificial intelligence (AI) systems to mitigate emerging attack vectors like indirect prompt injections and improve the overall security posture for agentic AI systems. "Unlike direct prompt injections, where an attacker directly inputs malicious commands into a prompt, indirect prompt injections involve hidden malicious instructions within external data sources," Google's GenAI security team said . These external sources can take the form of email messages, documents, or even calendar invites that trick the AI systems into exfiltrating sensitive data or performing other malicious actions. The tech giant said it has implemented what it described as a "layered" defense strategy that is designed to increase the difficulty, expense, and complexity required to pull off an attack against its systems. These efforts span model hardening, introducing purpose-built mac...

Cybersecurity researchers have discovered a novel attack technique called TokenBreak that can be used to bypass a large language model's (LLM) safety and content moderation guardrails with just a single character change. "The TokenBreak attack targets a text classification model's tokenization strategy to induce false negatives, leaving end targets vulnerable to attacks that the implemented protection model was put in place to prevent," Kieran Evans, Kasimir Schulz, and Kenneth Yeung said in a report shared with The Hacker News. Tokenization is a fundamental step that LLMs use to break down raw text into their atomic units – i.e., tokens – which are common sequences of characters found in a set of text. To that end, the text input is converted into their numerical representation and fed to the model.  LLMs work by understanding the statistical relationships between these tokens, and produce the next token in a sequence of tokens. The output tokens are detokeni...

Cybersecurity researchers have discovered an indirect prompt injection flaw in GitLab's artificial intelligence (AI) assistant Duo that could have allowed attackers to steal source code and inject untrusted HTML into its responses, which could then be used to direct victims to malicious websites. GitLab Duo is an artificial intelligence (AI)-powered coding assistant that enables users to write, review, and edit code. Built using Anthropic's Claude models, the service was first launched in June 2023. But as Legit Security found , GitLab Duo Chat has been susceptible to an indirect prompt injection flaw that permits attackers to "steal source code from private projects, manipulate code suggestions shown to other users, and even exfiltrate confidential, undisclosed zero-day vulnerabilities." Prompt injection refers to a class of vulnerabilities common in AI systems that enable threat actors to weaponize large language models (LLMs) to manipulate responses to user...

As the field of artificial intelligence (AI) continues to evolve at a rapid pace, fresh research has found how techniques that render the Model Context Protocol ( MCP ) susceptible to prompt injection attacks could be used to develop security tooling or identify malicious tools, according to a new report from Tenable. MCP, launched by Anthropic in November 2024, is a framework designed to connect Large Language Models (LLMs) with external data sources and services, and make use of model-controlled tools to interact with those systems to enhance the accuracy, relevance, and utility of AI applications. It follows a client-server architecture, allowing hosts with MCP clients such as Claude Desktop or Cursor to communicate with different MCP servers, each of which exposes specific tools and capabilities. While the open standard offers a unified interface to access various data sources and even switch between LLM providers, they also come with a new set of risks, ranging from exc...

Meta on Tuesday announced LlamaFirewall , an open-source framework designed to secure artificial intelligence (AI) systems against emerging cyber risks such as prompt injection, jailbreaks, and insecure code, among others. The framework , the company said, incorporates three guardrails, including PromptGuard 2, Agent Alignment Checks, and CodeShield. PromptGuard 2 is designed to detect direct jailbreak and prompt injection attempts in real-time, while Agent Alignment Checks is capable of inspecting agent reasoning for possible goal hijacking and indirect prompt injection scenarios. CodeShield refers to an online static analysis engine that seeks to prevent the generation of insecure or dangerous code by AI agents. "LlamaFirewall is built to serve as a flexible, real-time guardrail framework for securing LLM-powered applications," the company said in a GitHub description of the project. "Its architecture is modular, enabling security teams and developers to com...

Cybersecurity researchers have shed light on a new jailbreak technique that could be used to get past a large language model's (LLM) safety guardrails and produce potentially harmful or malicious responses. The multi-turn (aka many-shot) attack strategy has been codenamed Bad Likert Judge by Palo Alto Networks Unit 42 researchers Yongzhe Huang, Yang Ji, Wenjun Hu, Jay Chen, Akshata Rao, and Danny Tsechansky. "The technique asks the target LLM to act as a judge scoring the harmfulness of a given response using the Likert scale , a rating scale measuring a respondent's agreement or disagreement with a statement," the Unit 42 team said . "It then asks the LLM to generate responses that contain examples that align with the scales. The example that has the highest Likert scale can potentially contain the harmful content." The explosion in popularity of artificial intelligence in recent years has also led to a new class of security exploits called prompt in...

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,...

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...