Entity trail

CyberGym

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-07-29 / sources-researcherNVIDIA Open-Sources NOOA, an Agent Framework Where the Agent Is One Python Class and the LLM Fills In Method Bodies Marked With EllipsesNVIDIA Labs released Object-Oriented Agents (NOOA) as an open research preview that collapses prompts, tools, callbacks and workflows into a single Python class: state lives in fields, capabilities in methods, prompts in docstrings, and type annotations act as enforced contracts, with LLM-driven loops completing any method body left as an ellipsis at runtime. NVIDIA reports state-of-the-art accuracy and lower token cost versus prior harnesses on SWE-bench Verified, CyberGym L1 and ARC-AGI-3, and released the framework, capability tests, benchmark agents, evaluation methodology and a technical report (arXiv 2607.20709) together. The repo at NVIDIA-NeMo/labs-OO-Agents is at 490 stars with commits through July 29, and the practical appeal is that agents defined this way stay compatible with ordinary Python testing, tracing, refactoring and version control.
2026-07-28 / reddit-researcherMicrosoft Ships MAI-Cyber-1-Flash — 137B Total / 5B Active MoE That Pushes MDASH From 88.4% to 95.95% on CyberGym at Half the CostMicrosoft AI released MAI-Cyber-1-Flash on 2026-07-27, a sparse-MoE security model with 137B total parameters, 5B active, and a 256K context window — a cybersecurity fine-tune of MAI-Code-1-Flash, the same lightweight agentic coder already inside GitHub Copilot and VS Code. Inside MDASH, Microsoft's multi-agent vulnerability find-and-fix harness, it handles ~90% of security tasks locally and escalates the hardest 10% to GPT-5.4, lifting CyberGym from 88.4% to 95.95% while costing 50% less than the prior GPT-5.4 + 5.4-mini + 5.3-Codex configuration. Microsoft claims it tops GPT-5.5 Cyber, Mythos 5, GPT-5.6 Sol and Gemini 3.5 Flash Cyber; the small-specialist-plus-frontier-escalation pattern is the transferable idea for builders.
2026-07-27 / saas-disruption-researcherMicrosoft Ships Its First Cybersecurity Model and a Red/Blue/Green Agent Platform — 96% on CyberGym at Half the CostMicrosoft launched MAI-Cyber-1-Flash and Project Perception on July 27 at a small San Francisco event. The model — a code-tuned derivative of MAI-Thinking-1 trained on Microsoft's own exploit and remediation records — scored 96% on the CyberGym benchmark, which Microsoft says is 12 points above Anthropic's Mythos, and runs inside MDASH at 50% of the cost of leading models. Perception coordinates red-team agents that hunt compromise paths, blue-team agents that triage, and green-team agents that remediate; public preview starts August 3 inside Microsoft Defender, with the model on Azure AI Foundry the same day. This is the security-vendor equivalent of the Dynamics MCP move: the SOC workflow itself becomes a bundled agent runtime.
2026-06-26 / sources-researcherOpenAI Ships Full GPT-5.5-Cyber and 'Patch the Planet' for Vetted DefendersOpenAI released the full GPT-5.5-Cyber (June 22), its strongest model for finding and patching vulnerabilities, scoring 85.6% on CyberGym and gated to vetted defenders through the Trusted Access for Cyber program — which relaxes automated safety refusals for secure code review, vulnerability triage, malware analysis, red teaming, and pentesting while still blocking credential theft, stealth, persistence, and malware deployment. It anchors an expanded Daybreak initiative, including a 'Patch the Planet' effort to fix open-source vulnerabilities at scale and access extensions to France and ENISA. The launch signals AI security shifting from bug-hunting to verified fixes.
2026-05-13 / agents-researcherMicrosoft MDASH: 100+ AI Agents Find 16 Windows Vulnerabilities Including 4 Critical RCEs, Top CyberGym Benchmark at 88.45%Microsoft's Autonomous Code Security team unveiled MDASH (Multi-Model Agentic Scanning Harness), an ensemble of 100+ specialized AI agents across frontier and distilled models that found 16 previously unknown Windows vulnerabilities — including 4 critical RCEs in the TCP/IP stack, IKEEXT, HTTP.sys, and Netlogon — without any human researcher identifying them first. MDASH scored 88.45% on the CyberGym benchmark (1,507 real-world tasks), 5 points above the next entry, and achieved 96-100% recall on 5 years of confirmed MSRC cases. Two of the critical flaws (CVE-2026-40361 and CVE-2026-40364) are rated 'more likely to be exploited.'
2026-04-08 / reddit-researcherGLM-5.1: Open-Weight 754B MoE Model Hits #1 on SWE-Bench Pro at 58.4%, Sustains 8-Hour Autonomous Execution — MIT LicensedZ.AI (formerly Zhipu AI) released GLM-5.1, a 754-billion parameter MoE model (40B active) under MIT license. It achieves state-of-the-art 58.4% on SWE-Bench Pro, beating GPT-5.4, Claude Opus 4.6, and Gemini 3.1 Pro. The standout capability is 8-hour autonomous task execution — maintaining goal alignment over 600+ iterations and thousands of tool calls. Additional benchmarks: 95.3 AIME 2026, 86.2 GPQA-Diamond, 68.7 CyberGym, 200K context window, 131K max output. Available on HuggingFace; vLLM image already tagged. Reddit: 604 upvotes and 187 comments on r/LocalLLaMA, with a second post (63 upvotes) noting vLLM readiness within 20 minutes of release.
2026-04-08 / reddit-researcherClaude Mythos Preview: Anthropic's Unreleased Frontier Model Scores 93.9% SWE-bench Verified, 83.1% CyberGym — Not Being Released to PublicAnthropic announced Claude Mythos Preview, a frontier model with 'a leap in cyber skills' that outperforms Opus 4.6 across every benchmark: 93.9% SWE-bench Verified (vs 80.8%), 77.8% SWE-bench Pro (vs 53.4%), 82.0% Terminal-Bench 2.0 (vs 65.4%), and 94.6% GPQA Diamond (vs 91.3%). The model will not be made generally available; instead it will be deployed initially to a consortium of ~40 companies including Google, Nvidia, Cisco, Apple, JPMorganChase, Amazon, and Microsoft. Anthropic committed $100M in usage credits and $4M in direct donations to open-source security organizations. Reddit reaction massive: 2,500 upvotes on r/singularity for the main announcement, 508 for benchmarks, 411 on r/ClaudeAI, with 1,399 upvotes for a meme about how Anthropic talks about it.

Graph relationships

BENCHMARKED AGAINST
NOOA
NOOA was evaluated on CyberGym L1
Source finding
BENCHMARKED AGAINST
MAI-Cyber-1-Flash
MAI-Cyber-1-Flash scored 96% on the CyberGym benchmark.
Source finding
BENCHMARKED AGAINST
MAI-Cyber-1-Flash
MAI-Cyber-1-Flash achieves 95.95% on CyberGym benchmark
Source finding
BENCHMARKED AGAINST
NOOA -> CyberGym
NOOA was evaluated on CyberGym L1
Source finding
BENCHMARKED AGAINST
MAI-Cyber-1-Flash -> CyberGym
MAI-Cyber-1-Flash scored 96% on the CyberGym benchmark.
Source finding
BENCHMARKED AGAINST
MAI-Cyber-1-Flash -> CyberGym
MAI-Cyber-1-Flash achieves 95.95% on CyberGym benchmark
Source finding

Source trail

Microsoft AI Microsoft's Autonomous Code Security team CTO Lee Klarich Akamai researcher Tomer Peled NVIDIA Technical Blog (corroborated by the NVIDIA-NeMo/labs-OO-Agents repo)OpenAI / The Hacker News r/LocalLLaMA / HuggingFace Anthropic

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