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Microsoft and Wiz mind-meld agents catch more than 90% of bugs

What happened

Wiz is working to incorporate Google's Gemini model into its Project Atlas bug-hunting agent.

Source

Article excerpt

Security Secret to their success: Using the right model for the right security job Two agentic bug-hunting systems from Microsoft and Google-owned Wiz show that when it comes to finding and remediating software vulnerabilities, at least two models’ minds work better than one - and Wiz tells us it’s adding a third. Wiz on Monday said Project Atlas, its bug-hunting AI agent, bested Anthropic’s Mythos Preview and OpenAI’s GPT-5.5 Cyber with its vulnerability-analysis skills, achieving a 90.9 percent success rate on CyberGym, and uncovering more than 200 zero-day security holes in widely used open-source code. Meanwhile, Microsoft boasted its MDASH bug-hunting harness scored a 95.95 percent success rate on CyberGym, also beating Mythos, Gemini and GPT on the same benchmark for evaluating how well AI systems find real vulnerabilities in the code. For comparison, OpenAI’s GPT-5.5 Cyber scored 85.6 percent on CyberGym, and its GPT-5.6 Sol scored 83.6 percent. Anthropic’s Mythos 5 reproduced the target vulnerability on 83.8 percent of CyberGym challenges. And Google’s Gemini 3.5 Flash Cyber in CodeMender achieved an 83.2 percent success rate. The secret to both Atlas and MDASH’s success, according to the vendors, is that they use the right model for the right security job. Atlas uses Claude Opus 4.6 with GPT-5.5, Nir Ohfeld, head of vulnerability research at Wiz, told The Register...

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Extracted from this sentence

“We're now working to incorporate Gemini, which is well timed given Wiz's recent work with DeepMind on Gemini Flash Cyber,” he added.

Extracted by Autobound

From the Signal API record
Event
Integration

What this signalsA new integration often shows which tools the company builds around.

Product
Project Atlas

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The full record

From the Signal API record

Topics and mentions

Product tags

  • security
  • future tech

Extraction

Confidence
90%
Detected
Jul 28, 2026
signal_type
news
signal_subtype
integrates_with

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The API returns more than this page shows

This page shows a preview. The full news record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.

Company

  • linkedin_urlValue in the API
  • industriesValue in the API
  • employee_count_lowValue in the API
  • employee_count_highValue in the API
  • revenueValue in the API
  • descriptionValue in the API

Signal

  • signal_nameValue in the API
  • associationValue in the API
Show the full JSONThe record on this page and the API request

GET /v1/signals/3068acbb-f290-eb81-fb22-5caafebaff23 returns this record as JSON. POST /v1/companies/enrich returns every signal for wiz.io.

{
  "signal_id": "3068acbb-f290-eb81-fb22-5caafebaff23",
  "signal_type": "news",
  "signal_subtype": "integrates_with",
  "detected_at": "2026-07-28T19:21:01+00:00",
  "company": {
    "name": "Wiz",
    "domain": "wiz.io"
  },
  "data": {
    "url": "https://www.theregister.com/security/2026/07/28/microsoft-and-wiz-mind-meld-agents-catch-more-than-90-of-bugs/5279914",
    "title": "Microsoft and Wiz mind-meld agents catch more than 90% of bugs",
    "excerpt": "Security Secret to their success: Using the right model for the right security job Two agentic bug-hunting systems from Microsoft and Google-owned Wiz show that when it comes to finding and remediating software vulnerabilities, at least two models’ minds work better than one - and Wiz tells us it’s adding a third. Wiz on Monday said Project Atlas, its bug-hunting AI agent, bested Anthropic’s Mythos Preview and OpenAI’s GPT-5.5 Cyber with its vulnerability-analysis skills, achieving a 90.9 percent success rate on CyberGym, and uncovering more than 200 zero-day security holes in widely used open-source code. Meanwhile, Microsoft boasted its MDASH bug-hunting harness scored a 95.95 percent success rate on CyberGym, also beating Mythos, Gemini and GPT on the same benchmark for evaluating how well AI systems find real vulnerabilities in the code. For comparison, OpenAI’s GPT-5.5 Cyber scored 85.6 percent on CyberGym , and its GPT-5.6 Sol scored 83.6 percent. Anthropic’s Mythos 5 reproduced the target vulnerability on 83.8 percent of CyberGym challenges. And Google’s Gemini 3.5 Flash Cyber in CodeMender achieved an 83.2 percent success rate. The secret to both Atlas and MDASH’s success, according to the vendors, is that they use the right model for the right security job. Atlas uses Claude Opus 4.6 with GPT-5.5, Nir Ohfeld, head of vulnerability research at Wiz, told The Register...",
    "product": "Project Atlas",
    "summary": "Wiz is working to incorporate Google's Gemini model into its Project Atlas bug-hunting agent.",
    "planning": true,
    "image_url": "https://image.theregister.com/5279934.jpg?imageId=5279934&x=0&y=0&cropw=100&croph=100&panox=0&panoy=0&panow=100&panoh=100&width=1200&height=683",
    "confidence": 0.9,
    "product_data": {
      "name": "Project Atlas",
      "full_text": "Project Atlas",
      "fuzzy_match": false
    },
    "product_tags": [
      "security",
      "future_tech"
    ],
    "published_at": "2026-07-28T19:21:01Z",
    "article_sentence": "“We're now working to incorporate Gemini, which is well timed given Wiz's recent work with DeepMind on Gemini Flash Cyber,” he added.",
    "related_company_name": "Google",
    "related_company_domain": "google.com"
  }
}

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