Raw vector
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:LSummary
CVE-2026-28677 is a high-severity SSRF (CWE-918) vulnerability in Opensift Opensift. Its CVSS base score is 8.2 (High).
Operationally, exploitation aligns with the MITRE ATT&CK technique Exploit Public-Facing Application (T1190); ranked at the 22th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog.
This vulnerability is AI-related — categorised as Other Platforms; in the Supply Chain and Deployment risk domain.
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-2026-28677 is a server-side request forgery (SSRF) vulnerability, classified under CWE-918, affecting OpenSift prior to version 1.6.3-alpha. OpenSift is an AI study tool that processes large datasets via semantic search and generative AI. The issue resides in the URL ingest pipeline, which accepts user-controlled remote URLs but enforces incomplete destination restrictions. Although checks for private or localhost addresses exist, gaps in handling credentialed URLs, non-standard ports, and cross-host redirects enable SSRF abuse in non-localhost deployments. The vulnerability carries a CVSS v3.1 base score of 8.2 (AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:L) and was published on 2026-03-06.
Network-accessible attackers require no privileges or user interaction to exploit this flaw. By submitting crafted URLs to the ingest pipeline, they can evade restrictions and compel the server to issue requests to unintended internal destinations, such as services on non-standard ports or those requiring credentials. Successful exploitation yields high confidentiality impacts through unauthorized access to sensitive internal resources, alongside low availability effects, in affected non-localhost OpenSift instances.
Mitigation is available via upgrade to OpenSift version 1.6.3-alpha, where the issue has been patched. Supporting GitHub resources include patching commits at https://github.com/OpenSift/OpenSift/commit/1126e0a503876056a68a434e19f64158a5a4840b and https://github.com/OpenSift/OpenSift/commit/de99b9c, pull request #67, the release at https://github.com/OpenSift/OpenSift/releases/tag/v1.6.3-alpha, and the security advisory at https://github.com/OpenSift/OpenSift/security/advisories/GHSA-5jfc-p787-2mf9.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2026-9988
Vulnerability Data
OpenSift is an AI study tool that sifts through large datasets using semantic search and generative AI. Prior to version 1.6.3-alpha, the URL ingest pipeline accepted user-controlled remote URLs with incomplete destination restrictions. Although private/local host checks existed, missing restrictions…
more
for credentialed URLs, non-standard ports, and cross-host redirects left SSRF-class abuse paths in non-localhost deployments. This issue has been patched in version 1.6.3-alpha.
- CWE(s)
AI Security AnalysisAI
- AI Category
- Other Platforms
- Risk Domain
- Supply Chain and Deployment
- OWASP Top 10 for LLMs 2025
- None mapped
- Classification Reason
- Matched keywords: ai, generative ai
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.
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.
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.