CVE-2026-73032: Improper Control of Generation of Code ('Code Injection') in papersgpt papersgpt-for-zotero
PapersGPT for Zotero 0.6.1 contains a remote code execution vulnerability that allows attackers to execute arbitrary JavaScript by returning malicious code from an LLM endpoint that is passed unsanitized to window.eval() in views.ts. Attackers can exploit this through prompt injection in PDFs, MITM interception of API requests, or a malicious custom LLM endpoint to execute arbitrary code in Zotero's chrome-privileged context, enabling file read/write, process execution, and access to all Zotero data.
AI Analysis
Technical Summary
CVE-2026-73032 is a remote code execution vulnerability in PapersGPT for Zotero 0.6.1 caused by unsafe use of window.eval() on unsanitized JavaScript code returned from an LLM endpoint. Attackers can exploit this by injecting malicious prompts in PDFs, intercepting API requests, or providing a malicious LLM endpoint, resulting in arbitrary code execution within Zotero's privileged context. This allows attackers to read/write files, execute processes, and access all Zotero data. The vulnerability has a CVSS 4.0 score of 9.4, indicating critical severity. No patch or official fix has been disclosed as of the publication date.
Potential Impact
Exploitation of this vulnerability allows remote attackers to execute arbitrary JavaScript code in Zotero's chrome-privileged context, leading to full compromise of the Zotero environment. This includes the ability to read and write files on the host system, execute arbitrary processes, and access all user data managed by Zotero. The impact is critical due to the high level of access and control gained by an attacker without requiring privileges or user interaction beyond triggering the malicious code.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is available, users should avoid using untrusted LLM endpoints, be cautious with PDFs containing prompts processed by PapersGPT, and monitor for suspicious activity. No official remediation or temporary workaround has been published by the vendor at this time.
CVE-2026-73032: Improper Control of Generation of Code ('Code Injection') in papersgpt papersgpt-for-zotero
Description
PapersGPT for Zotero 0.6.1 contains a remote code execution vulnerability that allows attackers to execute arbitrary JavaScript by returning malicious code from an LLM endpoint that is passed unsanitized to window.eval() in views.ts. Attackers can exploit this through prompt injection in PDFs, MITM interception of API requests, or a malicious custom LLM endpoint to execute arbitrary code in Zotero's chrome-privileged context, enabling file read/write, process execution, and access to all Zotero data.
CVSS v4.0
Score 9.4critical
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
CVE-2026-73032 is a remote code execution vulnerability in PapersGPT for Zotero 0.6.1 caused by unsafe use of window.eval() on unsanitized JavaScript code returned from an LLM endpoint. Attackers can exploit this by injecting malicious prompts in PDFs, intercepting API requests, or providing a malicious LLM endpoint, resulting in arbitrary code execution within Zotero's privileged context. This allows attackers to read/write files, execute processes, and access all Zotero data. The vulnerability has a CVSS 4.0 score of 9.4, indicating critical severity. No patch or official fix has been disclosed as of the publication date.
Potential Impact
Exploitation of this vulnerability allows remote attackers to execute arbitrary JavaScript code in Zotero's chrome-privileged context, leading to full compromise of the Zotero environment. This includes the ability to read and write files on the host system, execute arbitrary processes, and access all user data managed by Zotero. The impact is critical due to the high level of access and control gained by an attacker without requiring privileges or user interaction beyond triggering the malicious code.
Mitigation Recommendations
Patch status is not yet confirmed — check the vendor advisory for current remediation guidance. Until an official fix is available, users should avoid using untrusted LLM endpoints, be cautious with PDFs containing prompts processed by PapersGPT, and monitor for suspicious activity. No official remediation or temporary workaround has been published by the vendor at this time.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- VulnCheck
- Date Reserved
- 2026-08-10T18:48:59.022Z
- Cvss Version
- 4.0
- State
- PUBLISHED
- Remediation Level
- null
Threat ID: 6a7b77a2bf8831d5394b40bb
Added to database: 08/11/2026, 19:27:30 UTC
Last enriched: 08/11/2026, 19:41:10 UTC
Last updated: 08/11/2026, 20:11:55 UTC
Views: 4
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