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{"bugzilla": {"description": "ragas: arbitrary file read via improper URL validation in multimodal inputs", "id": "2444875", "url": "https://bugzilla.redhat.com/show_bug.cgi?id=2444875"}, "csaw": false, "cvss3": {"cvss3_base_score": "7.5", "cvss3_scoring_vector": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N", "status": "draft"}, "cwe": "CWE-918", "details": ["An Arbitrary File Read vulnerability exists in the ImageTextPromptValue class in Exploding Gradients RAGAS v0.2.3 to v0.2.14. The vulnerability stems from improper validation and sanitization of URLs supplied in the retrieved_contexts parameter when handling multimodal inputs.", "A flaw was found in Ragas. Improper validation of URLs supplied in the retrieved_contexts parameter when handling multimodal inputs leads to Server-Side Request Forgery (SSRF). This vulnerability allows attackers to perform arbitrary file reads, conduct internal port scans and access cloud metadata."], "mitigation": {"lang": "en:us", "value": "To mitigate this vulnerability, implement strict input validation to filter out malicious payloads before passing the retrieved_contexts parameter to the Ragas evaluation pipeline. Specifically, enforce an allowlist that only accepts http:// or https:// URLs, explicitly rejecting the file:// scheme. Additionally, ensure the account running the Ragas process operates with principle of least privilege, restricting access to sensitive system files."}, "name": "CVE-2025-45691", "package_state": [{"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-llama-stack-core-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}, {"cpe": "cpe:/a:redhat:openshift_ai", "fix_state": "Not affected", "package_name": "rhoai/odh-trustyai-ragas-lls-provider-dsp-rhel9", "product_name": "Red Hat OpenShift AI (RHOAI)"}], "public_date": "2026-03-05T00:00:00Z", "references": ["https://www.cve.org/CVERecord?id=CVE-2025-45691\nhttps://nvd.nist.gov/vuln/detail/CVE-2025-45691\nhttps://adithyanak.com/ragas-v0214-arbitrary-file-read-vulnerability\nhttps://github.com/explodinggradients/ragas/blob/e97886ac976465efb60e5949c5d69baf30cc811d/src/ragas/prompt/multi_modal_prompt.py#L202\nhttps://github.com/explodinggradients/ragas/pull/1559\nhttps://github.com/vibrantlabsai/ragas/pull/1991"], "statement": "To exploit this flaw, an attacker needs to supply malicious input to a Ragas evaluation pipeline, typically by poisoning a dataset or submitting payloads directly via an API. This issue allows arbitrary file reads, internal port scans and access to cloud metadata, but it does not cause memory corruption or arbitrary command execution. Due to these reasons, this vulnerability has been rated with an important severity.", "threat_severity": "Important"}

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