VAITP

PlaywrightCapture stored capture-specific configuration and runtime data as mutable class-level variables rather than instance-level variables. Consequently, multiple Capture objects running within the same Python process could share state, including HTTP headers, cookies, browser storage, HTTP credentials, proxy configuration, user-agent settings, geolocation information, and captured request data. In a multi-user or concurrent deployment, information supplied during one capture could therefore persist and be reused by a subsequent or parallel capture. This could result in the disclosure of authentication cookies, credentials, browser storage, or captured request data belonging to another user. It could also cause requests to be performed with another capture's authentication context, headers, or proxy configuration, potentially enabling unauthorized access to remote resources or interference with other capture operations. The vulnerability is resolved by initializing all capture-specific settings and request data as instance variables in the Capture constructor, ensuring that state is isolated between capture operations.

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.

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.

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.

Strands Agents is an open-source Python SDK for building and running AI agents. The strands-agents-tools package provides pre-built tools for use with the SDK, including the elasticsearch_memory tool for agent memory storage. We identified CVE-2026-15746, a server-side request forgery (SSRF) issue in the elasticsearch_memory tool. The tool exposed its connection parameters (es_url, cloud_id, api_key) as fields the large language model (LLM) could control through the tool schema. When a caller omitted the api_key parameter, the tool fell back to the operator's ELASTICSEARCH_API_KEY environment variable and sent it to whichever host the LLM specified. A crafted prompt could cause the tool to connect to a threat-actor-controlled server and disclose the operator's Elasticsearch API key in the Authorization header. We recommend you upgrade to strands-agents-tools version 0.7.0 or later. As a precautionary measure, we recommend all operators rotate their ELASTICSEARCH_API_KEY, even if there is no indication the credential was exposed.

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.

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.

Tornado is a Python web framework and asynchronous networking library. Prior to 6.5.6, Tornado gzip decompression routines processed limited-size chunks but did not enforce an overall limit on accumulated decompressed chunks, allowing a malicious server accessed by SimpleAsyncHTTPClient or an HTTPServer configured with decompress_request=True to consume effectively unlimited memory. This issue is fixed in version 6.5.6.

Tornado is a Python web framework and asynchronous networking library. Prior to 6.5.6, SimpleAsyncHTTPClient shallow-copied redirected requests and removed only the Host header, leaving Authorization, auth_username, auth_password, and auth_mode in place when a redirect changed scheme, host, or port. This issue is fixed in version 6.5.6.

pyasn1 is a generic ASN.1 library for Python. Prior to 0.6.4, the univ.Real type converted its mantissa, base, and exponent value to a Python float using exact big-integer exponentiation. A BER, CER, or DER encoded REAL value only a few bytes long can carry a very large exponent, causing float conversion through prettyPrint(), str(), comparison, arithmetic, int(), or an explicit float() call to consume excessive CPU and memory and hang applications that decode untrusted ASN.1 data and then print, log, or compare decoded objects. This issue is fixed in version 0.6.4.