CVE-2025-1793
Official description Straight from the sourceThe vendor's or NVD's own wording, published unedited. Authoritative, but often terse — it says what broke, rarely what to do.
NVD · uneditedMultiple vector store integrations in run-llama/llama_index version v0.12.21 have SQL injection vulnerabilities. These vulnerabilities allow an attacker to read and write data using SQL, potentially leading to unauthorized access to data of other users depending on the usage of the llama-index library in a web application.
Technical summary Written by usOur analysis, written from the advisory, the CVSS vector and the affected-version data. It adds context the advisory leaves out, and never invents facts that are not in the source.
dbcve analysis · high confidenceSQL injection vulnerabilities exist in multiple vector store integrations of llama_index v0.12.21, where unsanitized user input in SQL queries enables attackers to read/write arbitrary data and potentially access other users' data in multi-tenant web applications.
Verify against the referenced sources before acting — the references below are authoritative for this CVE, this summary is not.
Affected products & versions What the vendor confirmedThe version ranges the vendor confirmed as vulnerable. If your version sits inside a range here, treat yourself as exposed until you have upgraded.
NVD · CPE data>= 0.12.21, < 0.12.28CVSS breakdown How the score is builtThe industry scoring standard. It rates how the flaw is reached, what it takes to exploit, and what an attacker gains — the score is derived from those, not the other way round.
From the vector- Attack vector
- Network
- Complexity
- Low
- Privileges
- None
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- High
- Integrity
- High
- Availability
- High
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
Am I affected? How to checkSteps we derive from the advisory and the affected-version data, so you can decide whether this CVE reaches your setup. They are a guide, not a scan — your own configuration is the authority.
dbcve checksWork through these to decide whether this CVE applies to you.
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Check installed llama_index versionRun 'pip show llama-index' or check your requirements.txt/poetry.lock for the installed version of llama_indexAffected if The installed version is >= 0.12.21 and < 0.12.28
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Identify vector store integrations in useSearch your codebase for imports from llama_index.vector_stores (e.g., 'from llama_index.vector_stores import') and list which vector store backends are being used (Chroma, Milvus, Pinecone, etc.)Affected if Any vector store integration from llama_index is being used with user-supplied input
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Verify input sanitization in vector store queriesSearch your code for places where user input (request parameters, form data, API payloads) is passed directly to vector store methods like query(), similarity_search(), or get_nodes() without validation or parameterized queriesAffected if User input flows directly to vector store query methods without sanitization or parameterization
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Check for SQL construction in vector store backendsIf using a SQL-backed vector store (e.g., PostgreSQL, MySQL vector stores), inspect the query construction code in your project or in the llama_index library to see if string interpolation is used for building queriesAffected if String interpolation or f-strings are used to build SQL queries from user input in vector store operations
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Audit multi-tenant data access patternsReview your application logic to determine if vector store queries could return data belonging to other tenants when different users submit queries (check for missing tenant_id filtering in query construction)Affected if The application is multi-tenant and tenant isolation is not enforced in vector store query logic
You are affected if you are using llama_index version 0.12.21 through 0.12.27 with vector store integrations and user input can reach those queries without sanitization.
Generated from the published advisory. Verify against your own configuration.
Remediation Closing itWhat it takes to close this. Where a vendor fix exists we point at it; where none exists we say so plainly, and can build one. Effort estimates are scoped from the advisory, not from your codebase.
dbcve · scoped0.12.28
Upgrade to a patched version of llama_index that implements proper SQL query parameterization and input sanitization in all vector store integrations; if unavailable, audit and manually parameterize all SQL queries in the affected integrations.
0.12.28 or later
- Check current LlamaIndex version: pip show llama-index or pip list | grep llama-index
- Upgrade to version 0.12.28 or later: pip install llama-index>=0.12.28
- Verify the upgrade was successful: pip show llama-index and confirm version is >= 0.12.28
- If using a virtual environment, restart any running applications to load the updated library
Generated from the published advisory — verify against the referenced sources before acting.
- Consultation4.0 h
- Implementation12.0 h
- Testing6.0 h
- Review / QA3.0 h
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Scan for this in your stack
Free · runs locallyCheck whether your project pulls in CVE-2025-1793 — or any other known-vulnerable package — straight from your lock files. Free and open source; it runs locally and uploads nothing.
References Go to the primary sourcePrimary sources — vendor advisories, patches and trackers. Where our summary and a reference disagree, the reference wins.
Primary sourcesPractitioner notes
ContributedPeer-ranked notes from engineers who’ve handled CVE-2025-1793 in production — separate from our analysis above.
The advisory tells you what broke. It rarely tells you what actually worked. If you’ve dealt with this one, that detail is what the next engineer is searching for.
- The version that genuinely resolved it — not the one the vendor claimed
- A config change or rule that shut the vector down
- A gotcha in the upgrade path that cost you an afternoon
No notes yet
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- Version or environment caveats, and links to real fixes
- No weaponised exploit code, or anything meant to cause harm
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