hono before 4.12.14 contains an html injection vulnerability in jsx server-side rendering that allows attackers to inject unintended html by using malformed attribute names. Attackers can craft specially crafted attribute keys containing characters like quotes or angle brackets to break html tag boundaries and inject arbitrary attributes or elements.
n8n before version 2.4.0 contains a sql injection vulnerability in MySQL, PostgreSQL, and Microsoft SQL nodes that allows authenticated users to inject arbitrary SQL through unescaped identifier values in node configuration parameters. Attackers with workflow creation permissions can supply specially crafted table or column names to execute unauthorized database commands and compromise data integrity.
n8n before 1.123.25 (1.x) and before 2.11.2 (2.x), with the fix also included in 2.12.0, contains a stored cross-site scripting vulnerability in the Form Trigger node's CSS sanitization that allows authenticated users to inject malicious scripts. Attackers with workflow creation permissions can inject XSS payloads that execute persistently for all form visitors, enabling form hijacking and phishing attacks.
ImageMagick before 7.1.2-15 contains a memory leak vulnerability in multiple coders that write raw pixel data where allocated objects are not properly freed. Attackers can trigger this leak by processing specially crafted images, causing memory exhaustion and denial of service.
ImageMagick before 7.1.2-19 contains an out-of-bounds access vulnerability in ConnectedComponentsImage() when processing connected-components artifacts with invalid indices. Attackers can trigger access violations by specifying malformed connected-components definitions via CLI, causing denial of service or potential code execution.
Crawl4AI before 0.8.7 contains an authentication bypass vulnerability in the monitor router endpoints that allows unauthenticated attackers to access destructive operations. Remote attackers can invoke the /monitor/actions/cleanup endpoint and manipulate monitoring state without authentication, causing service disruption.
Flowise before 3.1.0 (npm package flowise, versions 3.0.13 and earlier) uses a weak hardcoded default value 'Secre$t' for the TOKEN_HASH_SECRET environment variable in packages/server/src/enterprise/utils/tempTokenUtils.ts when the variable is not configured. This secret derives the AES-256-CBC key used to encrypt user IDs and workspace IDs in the 'meta' field of JWT tokens. An attacker who knows the default secret can decrypt this metadata to extract internal user and workspace identifiers, and re-encrypt manipulated values such as altered user or workspace IDs. Because the JWT signature is validated separately, decrypting or tampering with this metadata does not by itself grant access, but the disclosure of internal identifiers and possible metadata manipulation could aid privilege escalation or unauthorized data access.
Flowise before 3.1.0 (versions 3.0.13 and earlier) contains a missing authentication vulnerability in the /api/v1/loginmethod endpoint that allows unauthenticated users to retrieve an organization's complete SSO configuration, including OAuth client secrets in cleartext, by providing an organizationId parameter. Remote attackers can send a GET request to harvest sensitive API credentials for Google, Microsoft/Azure, GitHub, and Auth0 integrations. This affects FlowiseAI Cloud and self-hosted instances where the endpoint is exposed.
Flowise before 3.0.13 uses bcrypt with default salt rounds of 5, providing only 32 iterations instead of the OWASP-recommended minimum of 10 rounds. Attackers can crack password hashes approximately 30 times faster with modern GPU hardware, potentially compromising all user accounts in a database breach scenario.
Flowise through 2.2.7 contains a SQL injection vulnerability in the importChatflows API. Due to insufficient validation of the chatflow.id value, an authenticated user can supply a crafted JSON import file whose id field is concatenated unsanitized into a SQL IN clause, allowing arbitrary SQL to be executed, including blind and error-based extraction of data from the credential table.