PatchSiren

PatchSiren cyber security CVE debrief

CVE-2026-18647 jina-ai CVE debrief

CVE-2026-18647 is a server-side request forgery vulnerability in the jina-ai reader up to version 1574bfd380d249c86c82db4dace0d9c8fe17e2b1. The issue affects the function isValidTLD in the file /backend/functions/src/cloud-functions/crawler.ts of the component Crawler/Puppeteer. Remote exploitation of the attack is possible. The vendor was contacted but did not respond.

Vendor
jina-ai
Product
reader
CVSS
MEDIUM 5.5
CISA KEV
Not listed in stored evidence
Original CVE published
2026-08-03
Original CVE updated
2026-10-23
Advisory published
2026-08-03
Advisory updated
2026-10-23

Who should care

Defenders responsible for systems using the jina-ai reader component should assess their exposure to this vulnerability. Specifically, those managing systems with the Crawler/Puppeteer component should verify if their versions are affected and plan for mitigation or patching.

Why it matters

CVE-2026-18647 is a server-side request forgery vulnerability in the jina-ai reader that allows remote exploitation. Defenders should verify the presence of the vulnerable component, assess exposure, and monitor for patches or updates. The vulnerability's impact and remediation details require verification from official sources.

  • Remote exploitation of the vulnerability is possible, which could lead to unauthorized requests being made on behalf of the server.
  • The vulnerability's impact on the system requires verification from official sources due to limited information on affected or fixed versions.
  • Defenders need to verify the presence of the vulnerable component and assess its exposure to untrusted input.
  • The rolling release approach of the product means that version details for affected or updated releases are not provided.

Technical summary

The vulnerability is located in the isValidTLD function of the /backend/functions/src/cloud-functions/crawler.ts file in the Crawler/Puppeteer component of the jina-ai reader. This function is vulnerable to server-side request forgery (SSRF) attacks. The CVSS score for this vulnerability is 5.5, indicating a medium severity level. The vulnerability allows remote exploitation, which could lead to unauthorized requests being made on behalf of the server. Defenders should prioritize verifying the presence of this vulnerability in their systems and applying patches or mitigations as soon as they are available.

Defensive priority

Defenders should prioritize verifying the presence of this vulnerability in their systems and applying patches or mitigations as soon as they are available.

Recommended defensive actions

  • Verify the presence of the vulnerable component in your systems.
  • Assess the exposure of the component to untrusted input.
  • Monitor for patches or updates from the vendor.
  • Implement compensating controls to mitigate the vulnerability.
  • Review the supplied official advisory or CVE record to validate affected scope, severity, and vendor guidance.
  • Plan vendor-supported updates or mitigations through normal change control where exposure is confirmed.
  • Check relevant monitoring, detection, and logs for exposed assets that need extra review.

Evidence notes

The CVE record and NVD entry provide details about the vulnerability, including its description, CVSS score, and affected component. However, the vendor did not respond to the disclosure, and there is no information on fixed versions due to the rolling release approach.

Sources and references

Verified primary and authoritative sources

  • CVE-2026-18647 CVE Program record

    Publisher, destination, and source semantics verified

    URL: https://www.cve.org/CVERecord?id=CVE-2026-18647

    CVE Program - Official CVE Program record with source-provided CVE metadata.

  • CVE-2026-18647 NVD vulnerability detail

    Publisher, destination, and source semantics verified

    URL: https://nvd.nist.gov/vuln/detail/CVE-2026-18647

    NIST National Vulnerability Database - Official NIST NVD detail page and source-specific vulnerability assessment.

Supplemental references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.