Search: “OpenAI frontier models”

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DomainAll Cyber AIWindow24h 3d 7d 30d AllIn the wild Important only Show duplicates

CategoryAll AI safety & security 77 Vulnerability 65 AI industry 55 Exploit / PoC 41 Model release 24 Data breach 18 AI policy 16 Policy & legal 14 AI research 12 Threat actor 11 Ransomware 11 Industry 10 Malware 10 Tools 4

SeverityAll critical 104 high 34 medium 75 low 11 info 152

Introducing the CyberAgents Exchange AI Inspector: Rigorous review for community-built AI

Tenable and OpenAI launch the CyberAgents Exchange AI Inspector to security-review community-submitted AI agents, MCP servers, and skills using GPT Cyber models.

Tenable and OpenAI announced the CyberAgents Exchange AI Inspector, unveiled at OpenAI's "Intelligence at Work: Cyber Summit," to vet community-submitted AI agents, skills, MCP servers, and multi-agent playbooks in the CyberAgents Exchange registry. The process combines Tenable One AI Exposure scanning, OpenAI GPT Cyber model assessment, and human review, with reviews anchored to specific Git commits. The registry launched in August and hosts over 100 AI listings; the Inspector is expected to be available in September and has already detected prompt injection implemented via invisible Unicode tag characters in a SKILL.md file.

Tenable BlogSep 9, 13:00 UTC · 6d agoTools

Zscaler Agentic SOC combines AI agents with zero trust telemetry

Zscaler launched Agentic SOC, an AI-agent-driven security operations platform combining zero trust telemetry with frontier models from Anthropic and OpenAI.

Zscaler announced Agentic SOC, a security operations platform built around specialized AI agents for triage, root-cause investigation, verdict assignment, and automated threat containment. The platform pairs Zscaler's zero trust telemetry, drawn from roughly 750 billion daily transactions and a large decoy mesh network, with frontier models from Anthropic and OpenAI plus proprietary threat intelligence. It features closed-loop inline remediation that can isolate compromised users, block command-and-control traffic, and cut off lateral movement, alongside a context graph that correlates third-party data. Continuous threat hunting combines AI automation with human experts from Zscaler and Red Canary, and customer Maire Tecnimont is cited as an early adopter.

Help Net SecuritySep 9, 10:09 UTC · 7d agoTools

Proofpoint SOC Analyst Agent Uses OpenAI Cyber Models

Proofpoint launched its SOC Analyst Agent in private preview, using OpenAI Daybreak models to automate security investigations with human-controlled remediation, GA expected end of Q3 2026.

The SOC Analyst Agent uses OpenAI Daybreak cyber models to enable natural-language investigations across Proofpoint alerts, logs, DLP events and user risk signals, and to automate recurring threat hunts, data security investigations and escalation reporting. It is currently in private preview with general availability expected by the end of Q3 2026, and it does not independently make account changes or take remediation actions. Proofpoint joined the OpenAI Daybreak Defense Network in June 2026 and is exploring additional uses for the models in threat research, data security and AI security workflows.

Proofpoint Threat InsightSep 8, 21:23 UTC · 7d agoTools

OpenAI Builds ‘Defense Factory’ Where AI Agents Continuously Find and Fix Vulnerabilities

OpenAI unveils a Defense Factory where AI agents continuously discover, validate, and fix vulnerabilities, integrating GitHub, Snyk, Semgrep, Tenable, and ServiceNow.

OpenAI introduced a Defense Factory, an agent-first cybersecurity operation that connects AI agents to developer and security tools via APIs, CLIs, and Model Context Protocol integrations including GitHub, GitLab, Snyk, Semgrep, Tenable, Jira, Linear, and ServiceNow. During an internal security sprint, over 250 people across more than 100 service areas closed 53 urgent or high-priority issues on day one, achieved a 90.6% accepted ownership-assignment rate, and Codex generated all remediation patches with only 0.53% rolled back. Agent-assisted deduplication flagged 37% of findings as duplicates, and runtime validation reproduced 19.5% of findings, cutting the false-positive rate to 0.81%. OpenAI argues defenders must exploit a temporary 'defender's window' using source-code access and frontier models before open-weight models enable autonomous offensive agent fleets.

Cyber Security NewsSep 10, 10:36 UTC · 6d agoTools