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

A local attacker on a multi-user host can pre-create the deterministic cache path and plant a malicious ONNX model file. Spring AI 2.0.0 Spring AI 1.1.0 - 1.1.8 Spring AI 1.0.0 - 1.0.9

Analyzing a PDF with a deeply nested or cyclic table of contents can cause a StackOverflowError in the ingestion thread. Spring AI 2.0.0 Spring AI 1.1.0 - 1.1.8 Spring AI 1.0.0 - 1.0.9

In Spring AI's Semantic Cache support, the context hash used to isolate cached responses between different system prompts could allow cached responses to be shared across unrelated contexts. Affected versions: Spring AI: 2.0.0

The MCP Streamable HTTP server transport (WebFlux and WebMvc variants) does not place any limit on the number of sessions it retains, and by default does not require clients to be authenticated. As a result, a remote attacker can cause the server to accumulate an unbounded number of sessions over time, gradually exhausting available memory and ultimately causing a Denial of Service that affects all legitimate clients. Affected versions: Spring AI: 2.0.0

Spring AI's chat memory component contained a problematic default that, when not explicitly overridden, could result in unintended data exposure between users.

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 SpEL injection vulnerability exists in SimpleVectorStore when a user-supplied value is used as a filter expression key. A malicious actor could exploit this to execute arbitrary code. Only applications that use SimpleVectorStore and pass user-supplied input as a filter expression key are affected. This issue affects Spring AI: from 1.0.0 before 1.0.5, from 1.1.0 before 1.1.4.