Entity trail

AISLE AI

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

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-05-17 / thought-leaders-researcherAnthropic's Mythos Finds Thousands of Zero-Day Vulnerabilities but Less Than 1% Get PatchedDespite Claude Mythos uncovering thousands of high-severity vulnerabilities — including flaws 16 and 27 years old in open-source projects like FFmpeg maintained by small volunteer teams — CNBC reports fewer than 1% have been patched. Complicating the narrative, security firm Aisle demonstrated it could replicate Mythos's findings using older, cheaper, publicly available models. The gap between vulnerability discovery and remediation may be the real crisis, not the models themselves.
2026-05-09 / news-researcherCVE-2026-42511: 21-Year-Old Remote Code Execution Vulnerability Discovered in FreeBSDSecurity firm Aisle published a detailed breakdown of CVE-2026-42511, a remote code execution vulnerability that has existed in FreeBSD for 21 years. The discovery is connected to Anthropic's Project Glasswing, where Claude Mythos Preview autonomously identified and exploited the flaw without human involvement. The CVE underscores how AI-powered vulnerability scanning is finding bugs that two decades of human review missed.
2026-04-29 / hn-researcherAISLE AI Discovers 38 CVEs in OpenEMR Healthcare Software Used by 100K Providers — 172 Points on HNAI-native security platform AISLE found 38 CVEs in OpenEMR during Q1 2026, including two critical CVSS 10.0 SQL injection flaws that could enable full database compromise and PHI exfiltration across 200M+ patients. This accounted for more than half of all OpenEMR security advisories in the period. Fixes shipped in OpenEMR 8.0.0 (Feb 11, 2026), and AISLE PRO was integrated into OpenEMR's code review workflow in April. 172 points, 110 comments.
2026-04-12 / hn-researcherSmall Models Also Found the Vulnerabilities That Mythos Found — 1,113 Points on HN, #1 StoryAISLE founder Stanislav Fort published a counter-analysis showing that models as small as 3.6B parameters (GPT-OSS-20b at $0.11/Mtok) reproduced Mythos's cybersecurity findings, including a FreeBSD NFS exploit and a 27-year-old OpenBSD SACK bug. Small models actually outperformed frontier models on an OWASP false-positive test, correctly tracing Java data flow where Claude and GPT flagships failed. The conclusion: 'the moat in AI cybersecurity is the system, not the model' — capability doesn't scale smoothly with model size.
2026-04-10 / vibe-coding-researcherAISLE Research: Small Open-Weight LLMs Match Mythos on Vulnerability Detection — System Beats ModelAISLE tested Anthropic's Mythos-discovered vulnerabilities against 8 smaller open-weight models. All 8 — including GPT-OSS-20b at just 3.6B active params ($0.11/M tokens) — successfully detected the FreeBSD NFS exploit. On OWASP false-positive data flow tracing, DeepSeek R1 outperformed frontier models from Anthropic, OpenAI, and Google. The researchers conclude 'the moat in AI cybersecurity is the system, not the model' — orchestration and validation frameworks matter more than raw model capability.

Graph relationships

PARTNERS WITH
AISLE AI -> OpenEMR
AISLE PRO was integrated into OpenEMR's code review workflow in April 2026
Source finding
CRITICIZES
AISLE AI -> OpenEMR
AISLE AI discovered 38 CVEs in OpenEMR including two critical CVSS 10.0 SQL injection flaws
Source finding

Source trail

CNBC Aisle Security AISLE / Hacker News AISLE

Graph sources

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