Mercredi 15 juillet 2026

modelcontextprotocol python-sdk · Lfprojects mcp python sdk

The MCP Python SDK, called mcp on PyPI, is a Python implementation of the Model Context Protocol (MCP). Prior to 1.28.1, the deprecated mcp.server.websocket.websocket_server transport accepted WebSocket handshakes without applying Host or Origin header validation, leaving no SDK-level way to restrict which origins could connect to applications that exposed that transport. This issue is fixed in version 1.28.1.

modelcontextprotocol python-sdk · Lfprojects mcp python sdk

The MCP Python SDK, called mcp on PyPI, is a Python implementation of the Model Context Protocol (MCP). From 1.23.0 until 1.27.2, default handlers installed by server.experimental.enable_tasks() for tasks/list, tasks/get, tasks/result, and tasks/cancel operate only on task identifiers without recording the session that created each task, allowing any connected client to enumerate, read results from, consume messages for, or cancel other clients' tasks. This issue is fixed in version 1.27.2.

modelcontextprotocol python-sdk · Lfprojects mcp python sdk

The MCP Python SDK, called mcp on PyPI, is a Python implementation of the Model Context Protocol (MCP). Prior to 1.27.2, the SSE and stateful Streamable HTTP transports mcp.server.sse.SseServerTransport and mcp.server.streamable_http_manager.StreamableHTTPSessionManager route requests to existing sessions using only the session_id query parameter or Mcp-Session-Id header without verifying the authenticated principal that created the session, allowing a different bearer-token-authenticated client with a known session ID to inject JSON-RPC messages into that session. This issue is fixed in version 1.27.2.

MervinPraison PraisonAI

PraisonAI (praisonaiagents) before 1.6.78 contains a remote code execution vulnerability in the plugin manager, which loads and executes arbitrary Python (.py) files from project-level and user-home .praisonai/plugins/ directories using importlib spec_from_file_location() and exec_module() without code signing, integrity verification, or sandboxing. An attacker who can write a malicious .py file to a plugin directory (for example via path traversal, a supply chain attack, or a compromised dependency) achieves arbitrary code execution when the plugin system initializes.

MervinPraison PraisonAI

PraisonAI before 4.6.78 contains a remote code execution vulnerability in JobWorkflowExecutor._exec_inline_python() due to insufficient AST validation of workflow script steps. Attackers can create malicious YAML workflow files with import os statements followed by os.system() calls that bypass sandbox checks and execute arbitrary OS commands with process privileges.

MervinPraison PraisonAI

PraisonAI before 4.6.78 fails to safely encode deployment configuration values when generating Python source code for API servers. Attackers can inject arbitrary Python expressions through the deploy.api.host and agents_file configuration parameters that execute when the generated server starts or handles requests.