Keeping your data safe when an AI agent clicks a link
OpenAI published a blog post describing safeguards built into its AI agent systems to prevent URL-based data exfiltration and prompt injection attacks when agents follow links. The post outlines how OpenAI protects user data during agentic browsing or link-following actions. This addresses a known attack surface in autonomous agent deployments where malicious links could be used to leak context or hijack agent behavior.
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Designing AI agents to resist prompt injection
OpenAI published a blog post describing how ChatGPT's agent workflows are designed to resist prompt injection and social engineering attacks. The approach focuses on constraining risky actions and protecting sensitive data within agentic pipelines. This represents OpenAI's public articulation of defensive design principles for deployed AI agents.
Strengthening cyber resilience as AI capabilities advance
OpenAI published a post outlining its approach to cybersecurity risk as its models grow more capable, covering risk assessment frameworks, misuse mitigation, and collaboration with the security community. The piece addresses both offensive risk (AI-enabled attacks) and defensive applications. It represents OpenAI's public positioning on responsible deployment in a high-stakes domain.
Security on the path to AGI
OpenAI published a post outlining its approach to security as the organization advances toward AGI. The piece describes how security measures are being built directly into infrastructure and models proactively. The content is high-level and framing-oriented, with limited technical specifics visible in the excerpt.
Understanding prompt injections: a frontier security challenge
OpenAI has published a blog post addressing prompt injection attacks as a key security challenge for AI systems. The post covers how these attacks work and outlines OpenAI's multi-pronged approach including research, model training improvements, and safeguard development. This signals OpenAI's formal positioning on agentic security threats as their models are increasingly deployed in tool-using and autonomous contexts.
Disrupting Malicious Uses of AI
OpenAI published a report on its efforts to detect and disrupt malicious uses of its AI systems. The post covers threat actor activity identified and terminated on OpenAI's platform, including influence operations, cyberattack assistance, and other adversarial uses. It represents OpenAI's ongoing transparency reporting on abuse cases and countermeasures.
Disrupting Malicious Uses of AI: OpenAI June 2025 Report
OpenAI published its June 2025 report on detecting and preventing malicious uses of its AI systems. The report features case studies of threat actors attempting to abuse OpenAI's models and the countermeasures deployed. This is part of OpenAI's ongoing transparency series on adversarial misuse.
Disrupting Malicious Uses of AI | OpenAI Threat Report February 2026
OpenAI published its latest threat report examining how malicious actors are combining AI models with websites and social platforms for harmful purposes. The report analyzes detection and defense implications of these combined attack vectors. This represents OpenAI's ongoing effort to document and counter adversarial misuse of AI systems.
Preparing for future AI risks in biology
OpenAI has published a post outlining its proactive approach to assessing and mitigating biosecurity risks from advanced AI systems capable of biological applications. The piece describes capability evaluations and safeguards designed to prevent misuse of AI in biology and medicine. This reflects OpenAI's ongoing effort to get ahead of dual-use risks before capabilities reach dangerous thresholds.