Focus on opensift vulnerabilities and metrics.
Last updated: 08 Mar 2026, 23:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with opensift. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total opensift CVEs: 3
Earliest CVE date: 21 Feb 2026, 00:16 UTC
Latest CVE date: 21 Feb 2026, 00:16 UTC
Latest CVE reference: CVE-2026-27189
30-day Count (Rolling): 3
365-day Count (Rolling): 3
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): 0%
Year Variation (Calendar): 0%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): 0.0%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 3 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for opensift, sorted by severity first and recency.
OpenSift is an AI study tool that sifts through large datasets using semantic search and generative AI. Versions 1.1.2-alpha and below, use non-atomic and insufficiently synchronized local JSON persistence flows, potentially causing concurrent operations to lose updates or corrupt local state across sessions/study/quiz/flashcard/wellness/auth stores. This issue has been fixed in version 1.1.3-alpha.
OpenSift is an AI study tool that sifts through large datasets using semantic search and generative AI. In versions 1.1.2-alpha and below, URL ingest allows overly permissive server-side fetch behavior and can be coerced into requesting unsafe targets. Potential access/probing of private/local network resources from the OpenSift host process when ingesting attacker-controlled URLs. This issue has been fixed in version 1.1.3-alpha. To workaround when using trusted local-only exceptions, use OPENSIFT_ALLOW_PRIVATE_URLS=true with caution.
OpenSift is an AI study tool that sifts through large datasets using semantic search and generative AI. Versions 1.1.2-alpha and below render untrusted user/model content in chat tool UI surfaces using unsafe HTML interpolation patterns, leading to XSS. Stored content can execute JavaScript when later viewed in authenticated sessions. An attacker who can influence stored study/quiz/flashcard content could trigger script execution in a victim’s browser, potentially performing actions as that user in the local app session. This issue has been fixed in version 1.1.3-alpha.