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| CVE | CVSS | EPSS | Vendor, product | Description | Modified |
|---|---|---|---|---|---|
| CVE-2026-22738exploit ×2 | 9.8 critical | 1.0% | vmware, spring_ai | 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. | Mon 26 Oct |
| CVE-2026-59279 | 7.5 high | 1.0% | vmware, spring_ai | 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 | 16 Oct |
| CVE-2026-59318 | 9.8 critical | 0.00% | vmware, spring_ai | 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 1.0.9 | 15 Oct |
| CVE-2026-40978 | 8.8 high | 0.00% | vmware, spring_ai | 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) | Mon 26 Oct |
| CVE-2026-40967 | 8.6 high | 0.00% | vmware, spring_ai | 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) | Mon 26 Oct |
| CVE-2026-22742 | 8.6 high | 0.00% | vmware, spring_ai | 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. | Mon 26 Oct |
| CVE-2026-41713 | 8.2 high | 0.00% | vmware, spring_ai | 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. | Mon 26 Oct |
| CVE-2026-22743 | 7.5 high | 0.00% | vmware, spring_ai | 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. | Mon 26 Oct |
| CVE-2026-22744 | 7.5 high | 0.00% | vmware, spring_ai | 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. | Mon 26 Oct |
| CVE-2026-41712 | 7.5 high | 0.00% | vmware, spring_ai | Spring AI's chat memory component contained a problematic default that, when not explicitly overridden, could result in unintended data exposure between users. | Mon 26 Oct |
| CVE-2026-47835 | 7.5 high | 0.00% | vmware, spring_ai | 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). | Sun 25 Oct |
| CVE-2026-40980 | 6.5 medium | 0.00% | vmware, spring_ai | 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) | Mon 26 Oct |
| CVE-2026-40979 | 6.1 medium | 0.00% | vmware, spring_ai | 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) | Mon 26 Oct |
| CVE-2026-40966 | 5.9 medium | 0.00% | vmware, spring_ai | 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. | Mon 26 Oct |
| CVE-2026-94386 | 4.8 medium | 0.00% | no CPE yet | Use of Cache Containing Sensitive Information vulnerability in Apache Camel Oauth component. This issue affects Apache Camel: from 4.19.0 before 4.22.2. OAuthClientCredentialsTokenResolver obtains OAuth 2.0 bearer tokens through the client credentials grant on behalf of the components that authenticate their outbound calls with a named OAuth profile, such as camel-openai, camel-langchain4j-agent, camel-huggingface, camel-docling, camel-a2a, camel-spring-ai-chat and the IBM watsonx components, and of applications that call the OAuthClientAuthenticationFactory SPI directly. It kept the tokens it obtained in a static cache shared by every resolver instance and every CamelContext in the JVM, and keyed that cache on the token endpoint and the client ID only, although the token request also carries the client secret and the requested scope. Two profiles that share a token endpoint and a client ID but request different scopes, or authenticate with different client secrets, therefore mapped to the same cache entry: the profile that resolved a token first populated the entry, and the other profile was then handed that token, with no token request made under its own configuration, for as long as the token remained valid. Token caching is enabled by default, and pointing several profiles at one identity provider client is an ordinary use of the profile support rather than an opt-in to an insecure setting. The outcome is an outbound request that carries a token issued for another profile's scope, which can grant broader authority than the calling profile was configured for, or reach a service the token was not issued for; with identity providers that derive a token's audience from the requested scope, a different scope can mean a token for a different service altogether. A profile configured with a different client secret was likewise served the token obtained with the other secret, without authenticating with its own. The profiles are configured by the deployment, which is trusted, so no untrusted input reaches the cache: the party that gains is the service that receives a token it was not meant to receive, which, if hostile or compromised, can replay that token within its scope. Reaching the issue requires a deployment that defines more than one profile sharing a token endpoint and client ID while differing in scope or client secret. Users are recommended to upgrade to version 4.23.0, which fixes the issue. If users are on the 4.22.x releases stream, then they are suggested to upgrade to 4.22.2. The 4.19.x to 4.21.x release lines reached end of life before this issue was resolved and will not receive a fix, so deployments on them must move to a supported release. For deployments that cannot upgrade immediately, disable token caching on every OAuth profile that shares a token endpoint and client ID with another profile, by setting camel.oauth.NAME.cache-tokens=false for a named profile or camel.oauth.cache-tokens=false for the default one, so that each resolution requests a token with that profile’s own scope and client secret, at the cost of a token request on every resolution. Alternatively, register a separate client at the identity provider for each profile that needs a different scope or client secret, so that no two such profiles share a client ID. | Mon 26 Oct |
| CVE-2026-59308 | 4.3 medium | 0.00% | vmware, spring_ai | 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 | 16 Oct |
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EPSS scores: 2026-10-28. NVD cursor: 2026-10-29 00:22. The News page shows only notable CVEs (KEV, your stack, new criticals, EPSS over 50%, or active exploitation per SSVC); this table has all of them.