Spring Ai

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 2.0.0Show less

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 earlierShow less

In Spring AI's tool calling support, the per-request tool list is advertised to the model as a boundary but is not fully enforced when a tool call is dispatched. Under certain conditions, a tool that was not made available to the current request could be invoked, potentially leading to privilege escalation. Affected versions: Spring AI: 2.0.0 Spring AI: 1.1.0 through 1.1.8 Spring AI: 1.0.0 through 1.0.9Show less

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: 2.0.0Show less

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: 2.0.0Show less

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).Show less

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.xShow less

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.Show less

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.Show less

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)Show less

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)Show less

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.Show less

In Spring AI, various FilterExpressionConverter implementations accept a filter expression object and translate them to specific vector store query languages. In several cases, keys and values are not properly escaped, leading to the ability to alter the query. 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)Show less

In RedisFilterExpressionConverter of spring-ai-redis-store, when a user-controlled string is passed as a filter value for a TAG field, stringValue() inserts the value directly into the @field:{VALUE} RediSearch TAG block without escaping characters.This issue affects Spring AI: from 1.0.0 before 1.0.5, from 1.1.0 before 1.1.4.Show less

Spring AI's spring-ai-neo4j-store contains a Cypher injection vulnerability in Neo4jVectorFilterExpressionConverter. When a user-controlled string is passed as a filter expression key in Neo4jVectorFilterExpressionConverter of spring-ai-neo4j-store, doKey() embeds the key into a backtick-delimited Cypher property accessor (node.`metadata.`) after stripping only double quotes, without escaping embedded backticks.This issue affects Spring AI: from 1.0.0 before 1.0.5, from 1.1.0 before 1.1.4.Show less

Spring AI's spring-ai-bedrock-converse contains a Server-Side Request Forgery (SSRF) vulnerability in BedrockProxyChatModel when processing multimodal messages that include user-supplied media URLs. Insufficient validation of those URLs allows an attacker to induce the server to issue HTTP requests to unintended internal or external destinations. This issue affects Spring AI: from 1.0.0 before 1.0.5, from 1.1.0 before 1.1.4.Show less