Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:NSummary
CVE-2025-45691 is a high-severity Path Traversal (CWE-22) vulnerability in Vibrantlabsai Ragas. Its CVSS base score is 7.5 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 42th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
The strongest mitigations our analysis identified map to AC-3 (Access Enforcement) and AC-4 (Information Flow Enforcement) — see the control section below for these in your framework.
Deeper analysis AI-assisted summary
Synthesised by an AI model from the NVD description and linked references — a reading aid, not an authoritative source.
CVE-2025-45691 is an arbitrary file read vulnerability affecting the ImageTextPromptValue class in Exploding Gradients RAGAS versions 0.2.3 through 0.2.14. The issue arises from improper validation and sanitization of URLs provided in the retrieved_contexts parameter during handling of multimodal inputs, mapped to CWE-22 (path traversal). It carries a CVSS v3.1 base score of 7.5 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N), indicating high confidentiality impact with network accessibility, low attack complexity, no privileges or user interaction required.
A remote, unauthenticated attacker can exploit this vulnerability by supplying a malicious URL in the retrieved_contexts parameter, enabling arbitrary file reads on the host system running the affected RAGAS instance. Successful exploitation grants access to sensitive files, such as configuration data or other local resources, without impacting integrity or availability.
Advisories and patches reference a detailed analysis at https://adithyanak.com/ragas-v0214-arbitrary-file-read-vulnerability, the vulnerable code at https://github.com/explodinggradients/ragas/blob/e97886ac976465efb60e5949c5d69baf30cc811d/src/ragas/prompt/multi_modal_prompt.py#L202, and fixes via pull requests https://github.com/explodinggradients/ragas/pull/1559 and https://github.com/vibrantlabsai/ragas/pull/1991. Mitigation involves applying these patches or upgrading to a patched version of RAGAS beyond v0.2.14.
This vulnerability is notable in the context of AI/ML workflows, as RAGAS is a library used for evaluating retrieval-augmented generation applications. No public reports of real-world exploitation were identified at publication on 2026-03-05.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2025-208315
Vulnerability Data
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.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
—
—
—
V5.3.2V1.3.6V1.5.3V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Enforces the intended directory access authorizations that path traversal would otherwise bypass.
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly neutralizes special path elements before pathname construction occurs.
Least privilege reduces the impact of any unauthorized file access obtained via traversal.
Boundary protection limits the network reach of server-initiated requests even if SSRF occurs.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
Runtime monitoring of web applications and services can detect anomalous outbound requests indicative of SSRF.
Vulnerability identification processes can discover and record SSRF flaws in web applications.
Network segmentation and egress controls can limit the damage from successful SSRF requests.
Patching/maintenance can remediate known path-traversal flaws in deployed software (partial prevention of exploitability) but does nothing to stop the coding defect from being introduced in the first place.
PR.AA-05 defines and reviews access policies but does not address code-level pathname neutralization, so neither direction prevents CWE-22.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing in development catches path traversal via static/dynamic analysis.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.
Secure SDLC mandates input validation and path sanitization that directly prevent path traversal.
Application security requirements include rules for safe file handling and canonicalization.
Secure architecture principles require least-privilege file access and directory isolation.
Secure coding standards explicitly forbid unsafe path construction and mandate safe APIs.