This vulnerability allows remote attackers to execute arbitrary code on affected installations of OpenAI Codex. User interaction is required to exploit this vulnerability in that the target must visit a malicious page or open a malicious file. The ZDI has assigned a CVSS rating of 7.8. The following CVEs are assigned: CVE-2026-19592.

This vulnerability allows remote attackers to execute arbitrary code on affected installations of OpenAI Codex. User interaction is required to exploit this vulnerability in that the target must open a malicious folder. The ZDI has assigned a CVSS rating of 7.8. The following CVEs are assigned: CVE-2026-19591.

This vulnerability allows remote attackers to execute arbitrary code on affected installations of OpenAI Codex. User interaction is required to exploit this vulnerability in that the target must open a malicious folder. The ZDI has assigned a CVSS rating of 7.8. The following CVEs are assigned: CVE-2026-19591.

OpenAI Codex Desktop for Windows and macOS could execute attacker-controlled Git hooks because automated Git operations trusted the repository's local core.hooksPath setting. If a user opens an attacker-prepared repository whose preserved .git/config points core.hooksPath to an attacker-controlled directory, Codex can run a malicious hook while processing the repository. The hook executes outside Codex's command sandbox, without user approval, and with the user's privileges, allowing it to read, change, or delete the user's files and access other resources available to the user's account. An ordinary Git clone does not preserve the attacker-controlled repository-local configuration required for exploitation.

OpenAI Codex CLI for Windows, macOS, and Linux and Codex Desktop for Windows and macOS misclassified certain PowerShell commands as safe because their command-safety parser interpreted PowerShell's stop-parsing token (--%) differently than PowerShell itself. If a user opens an attacker-prepared repository and Codex follows its instructions, Codex can run a file-writing Git command without requesting user approval. On macOS and Linux, exploitation additionally requires separately installed PowerShell Core (pwsh) to be invoked. If filesystem protections permit the write, the command can modify Codex's configuration. If Codex later loads the modified configuration, it can launch an attacker-controlled MCP server and execute code with the user's privileges, allowing it to read, change, or delete files accessible to that account. The approval bypass does not disable filesystem sandboxing; the default filesystem sandbox on macOS and Linux can prevent writes outside permitted locations.

OpenAI Codex CLI for Windows, macOS, and Linux and Codex Desktop for Windows and macOS automatically collected Git repository metadata without disabling the repository-local core.fsmonitor setting. If a user opens or uses an attacker-prepared repository whose preserved .git/config sets core.fsmonitor to an attacker-controlled filesystem-monitor helper, Git can execute that helper while Codex collects repository metadata. The helper runs outside Codex's command sandbox and without a user-approval prompt, allowing attacker-controlled code to run with the user's privileges. The code can read, change, or delete the user's files and access other resources available to the user's account. An ordinary Git clone does not preserve the source repository's local .git/config; exploitation requires a repository delivered or copied with that configuration intact.

Pandora contains a path traversal vulnerability in its TAR archive extraction functionality. When processing a submitted TAR archive, the extractor passed archive member names directly to Python's tarfile.TarFile.extract() without applying an extraction filter.

An attacker able to submit a specially crafted TAR archive containing malicious member paths, such as paths using ../ sequences or absolute paths, could cause extracted files to be written outside the intended extraction directory. This may allow the attacker to overwrite files accessible to the Pandora worker process and could potentially result in application compromise, arbitrary code execution, or denial of service depending on the files targeted and the privileges of the Pandora process.

The vulnerability is corrected by using Python's filter='data' extraction filter, which rejects or sanitizes dangerous TAR members, including paths that escape the destination directory and unsafe link targets.

The weakness corresponds to MITRE's general path traversal category, which includes archive extraction cases where attacker-controlled filenames cause files to be written outside the intended directory.

Server-Side Request Forgery (SSRF) vulnerability in Drupal OpenAI Provider allows Server Side Request Forgery. This issue affects OpenAI Provider versions: from 0.0.0 to 1.1.1, from 1.2.0 to 1.2.2.

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.

A vulnerability was identified in OpenAI Codex CLI v0.23.0 and before that enables code execution through malicious MCP (Model Context Protocol) configuration files. The attack is triggered when a user runs the codex command inside a malicious or compromised repository. Codex automatically loads project-local .env and .codex/config.toml files without requiring user confirmation, allowing attackers to embed arbitrary commands that execute immediately.

OpenAI Atlas before 1.2025.288.15 exposed privileged browser APIs to web content on .openai.com origins. A cross-site scripting vulnerability in forum.openai.com could be used to access these functions, allowing access to browser history information and the ability to open or close tabs. OpenAI Atlas 1.2025.288.15 narrows access to these APIs to .chatgpt.com; users should upgrade to 1.2025.288.15 or later.

The Photos, Files, YouTube, Twitter, Instagram, TikTok, Ecommerce Contest Gallery – Upload, Vote, Sell via PayPal or Stripe, Social Share Buttons, OpenAI plugin for WordPress is vulnerable to Stored Cross-Site Scripting via the comment feature in all versions up to, and including, 26.1.0 due to insufficient input sanitization and output escaping. This makes it possible for unauthenticated attackers to inject arbitrary web scripts in pages that will execute whenever a user accesses an injected page.

Fullscreen API Spoofing and UI Redressing in the handling of Fullscreen API and UI rendering in OpenAI Operator SaaS on Web allows a remote attacker to capture sensitive user input (e.g., login credentials, email addresses) via displaying a deceptive fullscreen interface with overlaid fake browser controls and a distracting element (like a cookie consent screen) to obscure fullscreen notifications, tricking the user into interacting with the malicious site.

This vulnerability allows remote attackers to bypass the sandbox on affected installations of OpenAI Codex. User interaction is required to exploit this vulnerability in that the target must use Codex to process a repository containing malicious JavaScript. The ZDI has assigned a CVSS rating of 8.6.

This vulnerability allows remote attackers to bypass the sandbox on affected installations of OpenAI Codex. User interaction is required to exploit this vulnerability in that the target must use Codex to process a repository containing malicious JavaScript. The ZDI has assigned a CVSS rating of 8.6.

The Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI plugin for WordPress is vulnerable to time-based SQL Injection via the "getTermsForAjax" function in all versions up to, and including, 3.40.1. This is due to insufficient escaping on the user supplied parameters and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers, with contributor level access and above, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database granted they have metabox access for the taxonomy (enabled by default for contributors).

The Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI plugin for WordPress is vulnerable to SQL Injection via the 'posttypes' parameter in all versions up to, and including, 3.40.0 due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers, with Editor-level access and above, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.

This vulnerability allows remote attackers to execute arbitrary code on affected installations of GPT Academic. Authentication is not required to exploit this vulnerability. The specific flaw exists within the runinsubprocesswrapperfunc function. The issue results from the lack of proper validation of user-supplied data, which can result in deserialization of untrusted data. An attacker can leverage this vulnerability to execute code in the context of root.