RedisChatMemoryRepository.findByMetadata() builds RediSearch tag and text queries from caller-supplied metadata values without applying RediSearchUtil.escape(), unlike get(), clear(), and findByTimeRange() in the same class which do escape their inputs. An application that passes user-controlled values to findByMetadata() on a tag-typed metadata field allows an attacker to inject RediSearch syntax (e.g. x} | *) that breaks out of the tag clause and matches all indexed chat messages across every conversation in the index.
Spring AI 2.0.0
ResourceCacheService.getCacheName() builds the on-disk filename by appending the URI fragment verbatim, without stripping path separators or .. sequences, and passes the result to new File(resourceParentFolder, newFileName) before writing the downloaded bytes there.
Spring AI 2.0.0
Spring AI 1.1.0 - 1.1.8
Spring AI 1.0.9 and earlier
In Spring AI Vector Stores, special characters could be used to force the execution of arbitrary queries in Elasticsearch, OpenSearch, and GemFire VectorDB. Affected components: spring-ai-elasticsearch-store, spring-ai-opensearch-store, spring-ai-gemfire-store.
Affected versions:
Spring AI 1.0.0 through 1.0.x (fix 1.0.9).
Spring AI 1.1.0 through 1.1.x (fix 1.1.8).
Spring AI's support for Anthropic's Skills API used LLM-influenced filenames unsanitized in Path.resolve before writing files to disk. This could allow a malicious user to write files outside the intended target directory, including restricted directories.
Affected versions:
Spring AI: 1.1.0 through 1.1.x
Spring AI's chat memory component contained a problematic default that, when not explicitly overridden, could result in unintended data exposure between users.
A malicious user could craft input that is stored in conversation memory and later interpreted by the model in an unintended way. Applications using the affected advisor with user-controlled input may be susceptible to manipulation of model behavior across conversation turns.
Spring AI's MilvusVectorStore#doDelete(List) implementation is vulnerable to filter-expression injection via unsanitized document IDs.
Spring AI 1.0.x: affected from 1.0.0 through latest 1.0.x; upgrade to 1.0.7 or greater. Spring AI 1.1.x: affected from 1.1.0 through latest 1.1.x; upgrade to 1.1.6 or greater.
SQL injection vulnerability in Spring AI's `CosmosDBVectorStore` allows attackers to execute arbitrary SQL queries via crafted document IDs.
Affected versions:
Spring AI: 1.0.0 - 1.0.5 (fixed in 1.0.6), 1.1.0 - 1.1.4 (fixed in 1.1.5)
In Spring AI, having access to a shared environment can expose the ONNX model used by the application.
Affected versions:
Spring AI: 1.0.0 - 1.0.5 (fixed in 1.0.6), 1.1.0 - 1.1.4 (fixed in 1.1.5)
In Spring AI, a malicious PDF file can be crafted that triggers the allocation of unreasonable amounts of memory when handled by `ForkPDFLayoutTextStripper`.
Affected versions:
Spring AI: 1.0.0 - 1.0.5 (fixed in 1.0.6), 1.1.0 - 1.1.4 (fixed in 1.1.5)