{"slug": "261028-cve-intelligence-for-ai-builders", "title": "[261028] CVE Intelligence for AI Builders", "summary": "X-cmd published a CVE and CWE intelligence dataset for AI builders at x-cmd.com/cve, covering CVE records, CWE classifications, trend statistics and pre-aggregated analysis. Since 2024 the most common CWE types by CVE count are CWE-79 Cross-Site Scripting at 17,205, CWE-89 SQL Injection at 7,730, CWE-862 Missing Authorization at 6,336, CWE-74 Injection at 4,294, CWE-22 Path Traversal at 3,321 and CWE-94 Code Injection at 2,793. x-cmd advises AI builders to prioritize CWE-94 Code Injection, CWE-95 Eval Injection, CWE-502 Deserialization of Untrusted Data and CWE-917 Expression Language Injection, and to combine CVSS, EPSS and KEV when deciding remediation priority.", "body_md": "# CVE Intelligence for AI Builders\n\nTLDR\n\n- **Value** : x-cmd provides tailored CVE/CWE intelligence and trend stats for AI ecosystem security.\n- **Risks** : Guard against traditional flaws plus AI-specific threats like code injection (CWE-94), Eval injection (CWE-95), and deserialization (CWE-502).\n- **Application** : Combine CVSS, EPSS, and KEV for assessment, and use dependency scanners for remediation.\n\nIn the previous article, we discussed [Why AI builders need to pay attention to CVEs](https://www.x-cmd.com/blog/26/10/25/).\n\nNow, let's explore what this CVE data contains and how it can help developers observe security dynamics.\n\nThe number of publicly disclosed vulnerabilities has already reached hundreds of thousands, with new records added daily.\n\nRelying solely on an individual project's changelog makes it difficult to grasp overall security shifts across the ecosystem. By combining CVE and CWE data, we can uncover long-standing issues as well as emerging risk directions.\n\nWe have compiled a set of CVE intelligence data tailored for AI builders:\n\n`[x-cmd.com/cve](https://x-cmd.com/cve)`\n\nIt includes CVE records, CWE classifications, trend statistics, and pre-aggregated analytical insights.\n\n## What Can We See from CVE Data? \n\nThe latest CVE list helps developers understand recently emerged issues:\n\n- Which products have vulnerabilities;\n- What category of problem the vulnerability belongs to;\n- What the CVSS score is;\n- Whether it is associated with a specific CWE.\n\nHowever, a single vulnerability is merely an isolated event.\n\nAggregating massive volumes of CVEs reveals which vulnerability types consistently dominate the rankings.\n\n## Which Vulnerability Types Are Most Common? \n\nBased on CVE counts since 2024, top-ranking CWE types include:\n\n| CWE | Type | CVE Count | \n|---|---|---|\n| CWE-79 | Cross-Site Scripting (XSS) | 17,205 | \n| CWE-89 | SQL Injection | 7,730 | \n| CWE-862 | Missing Authorization | 6,336 | \n| CWE-74 | Injection | 4,294 | \n| CWE-22 | Path Traversal | 3,321 | \n| CWE-94 | Code Injection | 2,793 | \n\nThese vulnerability types are not new, but they persist over time.\n\nFor AI applications, traditional problems remain, while entirely new usage scenarios have also emerged.\n\nFor instance, when agents invoke tools, privilege boundaries must be considered; when executing model-generated code, isolated environments are necessary; when handling external content, input trustworthiness must be evaluated.\n\n## Which Vulnerability Types Should AI Builders Focus On? \n\nAI applications introduce workflows such as model outputs, tool invocations, and automated execution.\n\nSeveral CWE types are closely tied to the AI toolchain:\n\n- **CWE-94 (Code Injection)** : When agents execute generated code, attention must be paid to the execution environment and permission scopes.\n- **CWE-95 (Eval Injection)** : Dynamic execution patterns resembling`eval(user_input)` require extreme caution.\n- **CWE-502 (Deserialization of Untrusted Data)** : Handling external data can introduce inherent risks.\n- **CWE-917 (Expression Language Injection)** : Care is required when template engines render external content.\n\nThe common thread among these issues is that AI applications frequently feed model outputs, user inputs, and tool return values directly into subsequent execution pipelines.\n\n## Beyond Vulnerability Counts: Assessing Impact Level \n\nWhile CVE counts help observe trends, they do not directly equate to actual risk.\n\nDetermining whether a vulnerability requires priority remediation typically requires factoring in:\n\n- CVSS: The severity of the vulnerability impact;\n- EPSS: The probability of the vulnerability being exploited;\n- KEV: Whether actual attacks have been observed in the wild.\n\nAn issue with a low occurrence count that impacts a critical component may warrant higher priority than numerous low-risk vulnerabilities.\n\n## How Can This Data Be Used? \n\nThis data primarily serves several use cases:\n\nChecking technology stack risks.\n\nFor example, determining whether a specific framework, runtime, or toolchain has a history of public vulnerabilities.\n\nObserving security trends.\n\nFor instance, checking whether certain CWE types show long-term high frequencies or if novel risk categories are appearing within AI-related components.\n\nAssisting with vulnerability triage.\n\nCombining with tools like Dependabot, npm audit, pip-audit, or osv-scanner to further verify whether your project is affected.\n\nIt is not designed to replace dependency scanning tools, nor does it automatically know which specific version your project utilizes.\n\nInstead, it provides vulnerability intelligence and a trend perspective; specific remediation measures must still be determined based on your project's unique context.\n\n## Further Reading \n\nUpcoming topics will cover:\n\n- How CVE data is synchronized and curated;\n- How CWE classifications and rankings are generated;\n- How to query and analyze data using these insights.\n\nIf you are building AI applications, check out this CVE intelligence data to stay informed on recent vulnerability shifts and common risk categories.\n\nPlease indicate the source and link of this article when reprinting.\n\nHelp us make these docs great!\n\nAll X-CMD docs are generated from command help and multiple data sources. See something that's wrong or unclear? Feel free to let us know through any of these ways~", "url": "https://wpnews.pro/news/261028-cve-intelligence-for-ai-builders", "canonical_source": "https://www.x-cmd.com/blog/261028/", "published_at": "2026-10-28 00:00:00+00:00", "updated_at": "2026-11-11 02:52:34.485109+00:00", "lang": "en", "topics": ["ai-safety", "ai-tools", "developer-tools"], "entities": ["x-cmd", "CWE-79", "CWE-89", "CWE-94", "CWE-95", "CWE-502", "CWE-917", "CVSS"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/261028-cve-intelligence-for-ai-builders", "markdown": "https://wpnews.pro/news/261028-cve-intelligence-for-ai-builders.md", "text": "https://wpnews.pro/news/261028-cve-intelligence-for-ai-builders.txt", "jsonld": "https://wpnews.pro/news/261028-cve-intelligence-for-ai-builders.jsonld"}}