Jina Ai
Monthly
Server-side request forgery in jina-ai reader allows unauthenticated remote attackers to probe internal network infrastructure and cloud metadata services by exploiting a redirect-validation gap in the URL fetching pipeline. The service validates URLs on initial submission but fails to re-validate the destination after HTTP redirects, enabling attackers to pivot from an attacker-controlled public URL to cloud instance metadata endpoints (e.g., AWS IMDS at 169.254.169.254) or RFC-1918 internal addresses, with the response body returned to the attacker. No public exploit code has been independently confirmed at time of analysis, though a VulnCheck advisory and a public GitHub issue (jina-ai/reader#1252) detail the flaw.
Server-side request forgery in jina-ai reader allows unauthenticated remote attackers to reach cloud metadata services and internal HTTP endpoints by supplying publicly resolvable hostnames that map to private IP addresses. The private-address guard - intended to block RFC 1918 and metadata service IPs - is only enforced when the service runs inside Google Cloud, leaving all other deployment environments (AWS, Azure, on-premises) completely unprotected by this control. Successful exploitation in cloud-hosted deployments can yield instance metadata including IAM credentials and access tokens. No public exploit code has been identified at time of analysis, and this CVE is not currently listed in CISA KEV.
Server-side request forgery in jina-ai Reader's Puppeteer-based crawler allows unauthenticated remote attackers to manipulate the `isValidTLD` function to coerce the server into issuing arbitrary HTTP requests to internal or restricted network targets. All deployments up to commit 1574bfd380d249c86c82db4dace0d9c8fe17e2b1 are affected with no vendor-issued patch, as the maintainers did not respond to disclosure. A public proof-of-concept exploit exists (no CISA KEV listing), and the rolling release model means there is no safe pinned version for operators to target.
Server-side request forgery in jina-ai reader allows unauthenticated remote attackers to probe internal network infrastructure and cloud metadata services by exploiting a redirect-validation gap in the URL fetching pipeline. The service validates URLs on initial submission but fails to re-validate the destination after HTTP redirects, enabling attackers to pivot from an attacker-controlled public URL to cloud instance metadata endpoints (e.g., AWS IMDS at 169.254.169.254) or RFC-1918 internal addresses, with the response body returned to the attacker. No public exploit code has been independently confirmed at time of analysis, though a VulnCheck advisory and a public GitHub issue (jina-ai/reader#1252) detail the flaw.
Server-side request forgery in jina-ai reader allows unauthenticated remote attackers to reach cloud metadata services and internal HTTP endpoints by supplying publicly resolvable hostnames that map to private IP addresses. The private-address guard - intended to block RFC 1918 and metadata service IPs - is only enforced when the service runs inside Google Cloud, leaving all other deployment environments (AWS, Azure, on-premises) completely unprotected by this control. Successful exploitation in cloud-hosted deployments can yield instance metadata including IAM credentials and access tokens. No public exploit code has been identified at time of analysis, and this CVE is not currently listed in CISA KEV.
Server-side request forgery in jina-ai Reader's Puppeteer-based crawler allows unauthenticated remote attackers to manipulate the `isValidTLD` function to coerce the server into issuing arbitrary HTTP requests to internal or restricted network targets. All deployments up to commit 1574bfd380d249c86c82db4dace0d9c8fe17e2b1 are affected with no vendor-issued patch, as the maintainers did not respond to disclosure. A public proof-of-concept exploit exists (no CISA KEV listing), and the rolling release model means there is no safe pinned version for operators to target.