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

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

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)

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, an attacker can bypass conversation isolation and exfiltrate sensitive memory from other users’ chat histories, including secrets and credentials, by injecting filter logic through conversationId. Only applications that use VectorStoreChatMemoryAdvisor and pass user-supplied input as a conversationId are affected.