--- 格式版本: 2 标题: "Run a deep security scan – Codex Security | ChatGPT Learn" 原文链接: "https://developers.openai.com/codex/security/plugin/deep-scans" 发布日期: "2026-08-16" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:local:strict_original_body" 发布时间证据: "Published Time: Sun, 16 Aug 2026 07:39:24 GMT" 发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body" 发布时间校准置信度: "high" 发布时间候选数量: 4 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-08-17T00:08:18+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-08-16T23:54:06+08:00" 入库时间: "2026-08-16T16:08:18.947Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://developers.openai.com/blog" 匹配关键词: - "deployment" - "performance" - "latency" - "throughput" - "AI" 相关厂家: - "OpenAI" - "Microsoft" - "AWS" - "Google" - "Oracle" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 5 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "该页面为OpenAI Codex文档导航入口，内容为插件深度扫描的文档索引，未涉及超节点、AI Rack、机柜级基础设施等任何相关技术或商业信息，与项目主题完全无关。" AI质检模型: "ali-deepseek-v4-flash" AI质检时间: "2026-08-17T00:08:46+08:00" AI主题相关性: 0 AI来源权威性: 5 AI新颖性: 0 AI技术细节: 0 AI商业部署信号: 0 AI完整性: 0 AI摘要: "这篇OpenAI Codex安全插件文档的核心内容是介绍如何运行深度安全扫描，用于排查代码中的安全隐患。页面属于Codex安全配置指南的一部分，但正文未提供具体扫描参数、执行步骤或结果解读，主要包含开发者文档的导航结构。" AI摘要模型: "ali-deepseek-v4-flash" AI摘要时间: "2026-09-07T03:28:57.455Z" 采集批次: "2026年8月16日20点37分10秒" 采集批次ID: "20260816-203710-016" 去重键: "https://developers.openai.com/codex/security/plugin/deep-scans" --- Title: Run a deep security scan – Codex Security | ChatGPT Learn URL Source: https://developers.openai.com/codex/security/plugin/deep-scans Published Time: Sun, 16 Aug 2026 07:39:24 GMT Markdown Content: For the complete documentation index, see [llms.txt](https://developers.openai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to the page URL. 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[FAQ](https://developers.openai.com/codex/security/faq) ### Cyber safety * [Models & Trusted Access](https://developers.openai.com/codex/cyber-safety) * [Recommended configuration](https://developers.openai.com/codex/cyber-safety/recommended-configuration) Copy Page # Run a deep security scan Run a slower, more thorough review of a repository or scoped folder. Copy Page Run a deep scan when you need a more thorough review and can allow for a longer runtime. Deep scans search a repository more extensively and can reduce variability between runs. Start with a [standard scan](https://developers.openai.com/codex/security/plugin/scans) to check your scope and results. Then use a deep scan when you need a more thorough assessment. ## Choose between standard and deep scans | | Standard scan | Deep scan | | --- | --- | --- | | Best for | First runs and routine repository or folder review | More thorough reviews after a standard scan | | Variability | Standard | Reduced | | Scope | Repository or explicit folder | Repository or explicit folder | | Runtime and resources | Lower | Higher | | Pull requests and diffs | Use the change-review workflow | Not supported; use the change-review workflow instead | ## Configure deep-scan runtime To control a deep scan’s concurrency and duration, create or edit `~/.codex/codex-security/config.toml`. If you set `CODEX_HOME`, use `$CODEX_HOME/codex-security/config.toml` instead. For example, this profile runs a shorter scan with limited concurrency: ``` [deep_scan] workers = 2 subagents = 0 stop_after_no_new = 3 max_discovery_runs = 10 max_time_hours = 1.5 ``` | Setting | Default | Description | | --- | --- | --- | | `workers` | `auto` | Number of discovery workers allowed to run at the same time. Set a positive integer or `"auto"`. | | `subagents` | `3` | Number of subagents each discovery worker may start. Set `0` to disable them. | | `stop_after_no_new` | `6` | Stop discovery after this many consecutive runs produce no new candidates. | | `stop_after_consecutive_errors` | `3` | Stop discovery after this many consecutive worker errors. | | `max_discovery_runs` | `60` | Limit on discovery runs before the scan moves to validation. | | `max_time_hours` | `96` | Limit discovery to a positive number of hours up to `96`; use fractions as needed. | Lower values can reduce scan time and token use but may miss findings. Configuration changes apply to new deep scans, not scans already in progress. The time limit applies only to discovery. When it expires, Codex Security stops unfinished discovery, keeps completed results, and continues with validation and reporting. If no source review finishes before the deadline, the report records partial coverage. The `max_time_hours` setting requires plugin version `0.1.19` or later. See the [plugin changelog](https://developers.openai.com/codex/security/plugin/changelog) for release details. ## Start the deep scan In the desktop app, open **Security**, select **Scans**, and select **+ Scan**. Choose a repository or another folder, select **Codebase**, and turn on **Deep scan**. The scan covers the entire selected repository or folder. You can also start a repository-wide deep scan from a Codex conversation: `Use $codex-security:deep-security-scan to run a deep security scan of this repository.` For one component in a monorepo, identify the folder explicitly: `Use $codex-security:deep-security-scan to run a deep security scan of /absolute/path/to/repository/services/payments.` For a scoped deep scan in the desktop app, select the folder as the codebase. The scan covers the entire selected folder. ## Confirm setup and preflight For the best scan quality, use `gpt-5.6-sol` with `xhigh` reasoning effort. 1. Select **Codebase** and turn on **Deep scan**. 2. Confirm that the repository or selected folder is the code you intended to scan. 3. Choose a model and reasoning effort. 4. Open **Additional context** for concrete attack vectors, sensitive application areas, or repository context that the code can’t reveal. 5. Select **Start scan**. 6. Review any setup or capability warning before you approve a configuration change. Deep scans require delegated workers. If the current runtime doesn’t meet the capability requirements, use a standard scan or try again when enough capacity is available. Discovery workers inherit your selected model and reasoning settings. Follow the saved scan from **Scans**, or select **View activity** to inspect its Codex task. Check the [plugin changelog](https://developers.openai.com/codex/security/plugin/changelog) before you update the plugin or start a long-running scan. ![Image 2: Native Codex Security workbench showing a deep scan and its active review phase](https://developers.openai.com/_astro/deep-scan-progress.BlxbOwvb.webp)![Image 3: Native Codex Security workbench showing a deep scan and its active review phase](https://developers.openai.com/_astro/deep-scan-progress-dark.Dn5ccGFf.webp) ![Image 4: Native Codex Security workbench showing a deep scan and its active review phase](https://developers.openai.com/_astro/deep-scan-progress.BlxbOwvb.webp)![Image 5: Native Codex Security workbench showing a deep scan and its active review phase](https://developers.openai.com/_astro/deep-scan-progress-dark.Dn5ccGFf.webp) Track the active deep-scan phase and inspect its Codex activity before reviewing the completed result. ## Review the result Deep scans use the same saved scan details and complete scan directory as standard scans. Open the completed scan in **Scans** or review its findings in **Findings**. The generated `report.md` links to detailed vulnerability reports or structural hardening guidance when you request those outputs. Keep any linked `findings/` and `hardening/` directories with the report when sharing or archiving the result. Review the coverage summary before the findings. Even a deep scan has limits, so check deferred surfaces and remaining proof gaps before drawing a conclusion. For a finding you accept, continue with [Fix and verify a finding](https://developers.openai.com/codex/security/plugin/fix-findings). To review a pull request, commit, branch range, or local patch, use [Review code changes](https://developers.openai.com/codex/security/plugin/code-changes). A deep scan never substitutes for the diff-focused workflow. 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