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Information ExposureWeakness · CWE-200

CVE-2026-14898

MEDIUM · 6.5 CVSS v3.1 Published 2026-07-06
Mitigation only
No fix yet — a mitigation exists. There is no fixed release. A documented workaround reduces exposure in the meantime.
See remediation →
72/100
Remediation priority · Elevated
Remotely reachable No privileges 6 weeks old

Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.

NVD · unedited
The OpenAI Codex desktop app for macOS rendered remote images from Markdown in model responses. An attacker who could place an indirect prompt injection in content processed by Codex, such as a connected-tool result or another untrusted source, could induce the model to construct a remote image URL containing sensitive data. The app automatically fetched that URL when rendering the response, sending the embedded data to an attacker-controlled server without a separate user click. Successful exploitation could exfiltrate secrets and other information accessible in the Codex session, including API keys, source code, and data returned by connected tools. No direct integrity or availability impact was demonstrated, and there is no known exploitation in the wild.

In the news

Third-party coverage
Trending covered by 1 outlet this week · latest 4d ago

Surfaced from public web coverage — external links open in a new tab.

Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.

dbcve analysis · high confidence

The OpenAI Codex desktop app for macOS automatically fetches and renders remote images from Markdown in model responses without user confirmation. An attacker can exploit indirect prompt injection in untrusted content (e.g., connected-tool results) to cause the model to generate image URLs containing embedded sensitive data (API keys, source code, tool outputs). The app automatically requests these URLs during rendering, exfiltrating session data to an attacker-controlled server without any user interaction.

MitigationDisable automatic remote image fetching in Markdown rendering and implement output sanitization to detect or block URLs containing embedded sensitive data before rendering.

Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.

CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.

From the vector
Attack vector
Network
Complexity
Low
Privileges
None
User interaction
Required
Scope
Unchanged
Confidentiality
High
Integrity
None
Availability
None

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:N/A:N

Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.

dbcve checks

Work through these to decide whether this CVE applies to you.

  1. Confirm OpenAI Codex desktop app is installed
    Check for the app in /Applications folder or via 'ls /Applications | grep -i codex' in Terminal. Also check via Spotlight search.
    Affected if The OpenAI Codex desktop app for macOS is installed and running
  2. Identify the installed version
    Right-click the Codex app in Applications, select Get Info, or run 'mdls -name kMDItemVersion "/Applications/OpenAI Codex.app"' in Terminal. Compare against any published affected versions.
    Affected if The installed version falls within an affected range (if known) or is an unpatched version
  3. Check for automatic image loading in settings
    Open Codex preferences/settings panel and look for options related to Markdown rendering, image display, or remote content fetching. Check ~/Library/Preferences/com.openai.codex.plist for relevant boolean keys.
    Affected if Automatic remote image fetching in Markdown rendering is enabled (default behavior)
  4. Inspect network traffic for unexpected image requests
    Use a network monitor (e.g., Little Snitch, nettop, or Charles Proxy) to observe outbound HTTP requests from the Codex app. Look for requests to unfamiliar domains containing encoded data in URL paths.
    Affected if The app is making HTTP GET requests to URLs containing sensitive data (API keys, tokens, code) without user interaction

A user is affected if they have the OpenAI Codex desktop app for macOS with automatic remote image fetching enabled, as hidden image URLs in model responses can exfiltrate sensitive session data to attacker-controlled servers.

Generated from the published advisory. Verify against your own configuration.

Check your environment

Paste your version and any relevant configuration and it will be compared against the affected criteria above. Do not include secrets or credentials.

AI-assisted, checked against the advisory. Informational, not a guarantee.

Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.

From vendor data
Mitigation available No clean upgrade yet — mitigate in the meantime
Mitigation

Disable automatic remote image fetching in Markdown rendering and implement output sanitization to detect or block URLs containing embedded sensitive data before rendering.

Have this fixed Scoped from the published advisory
  • Consultation2.0 h
  • Implementation8.0 h
  • Testing4.0 h
  • Review / QA2.0 h
16.0 hours of engineering $2,800
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References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.

Primary sources

Practitioner notes

Contributed

Peer-ranked notes from engineers who’ve handled CVE-2026-14898 in production — separate from our analysis above.

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What this is

A place for practitioners to share what actually worked: a mitigation you’ve tested, a configuration change, a version- or environment-specific caveat, or a link to a verified patch. The most useful notes rise to the top as peers upvote them, so the signal stays high.

What belongs here
  • Verified mitigations, workarounds, and config changes
  • Version or environment caveats, and links to real fixes
  • No weaponised exploit code, or anything meant to cause harm
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