Chamilo LMS is a learning management system. Prior to 2.0.0-RC.3, a Reflected Cross-Site Scripting (XSS) vulnerability in the exercise question list admin panel allows an attacker to execute arbitrary JavaScript in an authenticated teacher's browser. The pagination code merges all $_GET parameters via array_merge() and outputs the result via http_build_query() directly into HTML href attributes without htmlspecialchars() encoding. This vulnerability is fixed in 2.0.0-RC.3.
Chamilo LMS is a learning management system. From 1.11.0 to 2.0-beta.1, anyone can trigger a malicious redirect through the use of the redirect parameter to /login. This vulnerability is fixed in 2.0-beta.2.
Vikunja is an open-source self-hosted task management platform. Prior to 2.3.0, Vikunja's scoped API token enforcement for custom project background routes is method-confused. A token with only projects.background can successfully delete a project background, while a token with only projects.background_delete is rejected. This is a scoped-token authorization bypass. This vulnerability is fixed in 2.3.0.
PraisonAI is a multi-agent teams system. Prior to 4.5.128, PraisonAI automatically loads a file named tools.py from the current working directory to discover and register custom agent tools. This loading process uses importlib.util.spec_from_file_location and immediately executes module-level code via spec.loader.exec_module() without explicit user consent, validation, or sandboxing. The tools.py file is loaded implicitly, even when it is not referenced in configuration files or explicitly requested by the user. As a result, merely placing a file named tools.py in the working directory is sufficient to trigger code execution. This behavior violates the expected security boundary between user-controlled project files (e.g., YAML configurations) and executable code, as untrusted content in the working directory is treated as trusted and executed automatically. If an attacker can place a malicious tools.py file into a directory where a user or automated system (e.g., CI/CD pipeline) runs praisonai, arbitrary code execution occurs immediately upon startup, before any agent logic begins. This vulnerability is fixed in 4.5.128.
PraisonAI is a multi-agent teams system. Prior to 4.5.128, cmd_unpack in the recipe CLI extracts .praison tar archives using raw tar.extract() without validating archive member paths. A .praison bundle containing ../../ entries will write files outside the intended output directory. An attacker who distributes a malicious bundle can overwrite arbitrary files on the victim's filesystem when they run praisonai recipe unpack. This vulnerability is fixed in 4.5.128.
PraisonAI is a multi-agent teams system. Prior to 4.5.128, PraisonAI's AST-based Python sandbox can be bypassed using type.__getattribute__ trampoline, allowing arbitrary code execution when running untrusted agent code. The _execute_code_direct function in praisonaiagents/tools/python_tools.py uses AST filtering to block dangerous Python attributes like __subclasses__, __globals__, and __bases__. However, the filter only checks ast.Attribute nodes, allowing a bypass. The sandbox relies on AST-based filtering of attribute access but fails to account for dynamic attribute resolution via built-in methods such as type.getattribute, resulting in incomplete enforcement of security restrictions. The string '__subclasses__' is an ast.Constant, not an ast.Attribute, so it is never checked against the blocked list. This vulnerability is fixed in 4.5.128.
PraisonAI is a multi-agent teams system. Prior to 4.5.128, PraisonAI’s MCP (Model Context Protocol) integration allows spawning background servers via stdio using user-supplied command strings (e.g., MCP("npx -y @smithery/cli ...")). These commands are executed through Python’s subprocess module. By default, the implementation forwards the entire parent process environment to the spawned subprocess. As a result, any MCP command executed in this manner inherits all environment variables from the host process, including sensitive data such as API keys, authentication tokens, and database credentials. This behavior introduces a security risk when untrusted or third-party commands are used. In common scenarios where MCP tools are invoked via package runners such as npx -y, arbitrary code from external or potentially compromised packages may execute with access to these inherited environment variables. This creates a risk of unintended credential exposure and enables potential supply chain attacks through silent exfiltration of secrets. This vulnerability is fixed in 4.5.128.
PraisonAIAgents is a multi-agent teams system. Prior to 1.5.128, web_crawl's httpx fallback path passes user-supplied URLs directly to httpx.AsyncClient.get() with follow_redirects=True and no host validation. An LLM agent tricked into crawling an internal URL can reach cloud metadata endpoints (169.254.169.254), internal services, and localhost. The response content is returned to the agent and may appear in output visible to the attacker. This fallback is the default crawl path on a fresh PraisonAI installation (no Tavily key, no Crawl4AI installed). This vulnerability is fixed in 1.5.128.
SvelteKit is a framework for rapidly developing robust, performant web applications using Svelte. Prior to 2.57.1, under certain circumstances, requests could bypass the BODY_SIZE_LIMIT on SvelteKit applications running with adapter-node. This bypass does not affect body size limits at other layers of the application stack, so limits enforced in the WAF, gateway, or at the platform level are unaffected. This vulnerability is fixed in 2.57.1.
SvelteKit is a framework for rapidly developing robust, performant web applications using Svelte. Prior to 2.57.1, redirect, when called from inside the handle server hook with a location parameter containing characters that are invalid in a HTTP header, will cause an unhandled TypeError. This could result in DoS on some platforms, especially if the location passed to redirect contains unsanitized user input. This vulnerability is fixed in 2.57.1.