Raw vector
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:L/VA:N/SC:L/SI:L/SA:L/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:XCVSS and EPSS are reproduced from their sources (NVD, FIRST EPSS). Risk Priority is our own derived reading, not an NVD score.
Summary
CVE-2026-34504 is a medium-severity SSRF (CWE-918) vulnerability in Openclaw Openclaw. Its CVSS base score is 6.9 (Medium).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 14th 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-4 (Information Flow Enforcement) and SI-10 (Information Input Validation) — 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-2026-34504 is a server-side request forgery (SSRF) vulnerability (CWE-918) affecting OpenClaw versions prior to 2026.3.28. The issue resides in the fal provider's image-generation-provider.ts component, where unguarded image download fetches enable attackers to make requests to internal URLs. This flaw has a CVSS v3.1 base score of 8.3 (AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:L), indicating high severity due to its network accessibility, low complexity, lack of required privileges or user interaction, and scope expansion.
A malicious or compromised fal relay can exploit this vulnerability by leveraging the image pipeline to fetch internal service metadata and responses. Attackers require the ability to interact with the fal provider but face no authentication barriers, allowing remote exploitation over the network to indirectly access and exfiltrate sensitive internal resources.
Mitigation is addressed in OpenClaw version 2026.3.28 and later, with a specific patch available in GitHub commit 80d1e8a11a2ac118c7f7a70bba9c862b6141d928. Security practitioners should consult the official GitHub security advisory (GHSA-qxgf-hmcj-3xw3) and VulnCheck advisory for detailed remediation steps and verification guidance.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-17471
Vulnerability Data
OpenClaw before 2026.3.28 contains a server-side request forgery vulnerability in the fal provider image-generation-provider.ts component that allows attackers to fetch internal URLs. A malicious or compromised fal relay can exploit unguarded image download fetches to expose internal service metadata and…
more
responses through the image pipeline.
- CWE(s)
Related Threats
MITRE ATT&CK Enterprise Techniques
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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V1.3.6V1.5.3V5.3.2V10.4.7
Mitigating Controls (NIST 800-53 r5) AI
Information flow enforcement can restrict which destinations the server is allowed to contact on behalf of users.
Input validation directly stops untrusted URLs from being accepted and fetched without destination checks.
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.
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.
Secure development practices directly include input validation and destination allow-listing that prevent SSRF.
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.
Operational threat data describing SSRF campaigns can be used to tighten outbound-request allow-lists and detection rules before attackers exploit them.