prompt injection

  • ChatGPT Faces New Data-Pilfering Attack


    ChatGPT falls to new data-pilfering attack as a vicious cycle in AI continuesOpenAI has implemented restrictions on ChatGPT to prevent data-pilfering attacks like ShadowLeak by limiting the model's ability to construct new URLs. Despite these measures, researchers developed the ZombieAgent attack by providing pre-constructed URLs, which allowed data exfiltration letter by letter. OpenAI has since further restricted ChatGPT from opening links that originate from emails unless they are from a well-known public index or directly provided by the user. This ongoing cycle of attack and mitigation highlights the persistent challenge of securing AI systems against prompt injection vulnerabilities, which remain a significant threat to organizations using AI technologies. Guardrails are temporary fixes, not fundamental solutions, to these security issues. This matters because it underscores the ongoing security challenges in AI systems, emphasizing the need for more robust solutions to prevent data breaches and protect sensitive information.

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  • Building a Self-Testing Agentic AI System


    A Coding Implementation to Build a Self-Testing Agentic AI System Using Strands to Red-Team Tool-Using Agents and Enforce Safety at RuntimeAn advanced red-team evaluation harness is developed using Strands Agents to test the resilience of tool-using AI systems against prompt-injection and tool-misuse attacks. The system orchestrates multiple agents to generate adversarial prompts, execute them against a guarded target agent, and evaluate responses using structured criteria. This approach ensures a comprehensive and repeatable safety evaluation by capturing tool usage, detecting secret leaks, and scoring refusal quality. By integrating these evaluations into a structured report, the framework highlights systemic weaknesses and guides design improvements, demonstrating the potential of agentic AI systems to maintain safety and robustness under adversarial conditions. This matters because it provides a systematic method for ensuring AI systems remain secure and reliable as they evolve.

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  • AI and Cloud Security Failures of 2025


    Supply chains, AI, and the cloud: The biggest failures (and one success) of 2025Recent developments in AI and cloud technologies have highlighted significant security vulnerabilities, particularly in the realm of supply chains. Notable incidents include AI-related attacks such as a prompt injection on GitLab's Duo chatbot, which led to the insertion of malicious code and data exfiltration, and a breach involving the Gemini CLI coding tool that allowed attackers to execute harmful commands. Additionally, hackers have exploited AI chatbots to enhance the stealth and effectiveness of their attacks, as seen in cases involving the theft of sensitive government data and breaches of platforms like Salesloft Drift AI, which compromised security tokens and email access. These events underscore the critical need for robust cybersecurity measures as AI and cloud technologies become more integrated into business operations. This matters because the increasing reliance on AI and cloud services demands heightened vigilance and improved security protocols to protect sensitive data and maintain trust in digital infrastructures.

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  • OpenAI’s Challenge with Prompt Injection Attacks


    OpenAI Admits This Attack Can't Be StoppedOpenAI acknowledges that prompt injection attacks, a method where malicious inputs manipulate AI behavior, are a persistent challenge that may never be completely resolved. To address this, OpenAI has developed a system where AI is trained to hack itself to identify vulnerabilities. In one instance, an agent was manipulated into resigning on behalf of a user, highlighting the potential risks of these exploits. This matters because understanding and mitigating AI vulnerabilities is crucial for ensuring the safe deployment of AI technologies in various applications.

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