VAITP

Kiota is an OpenAPI based HTTP Client code generator. Prior to 1.32.0, Kiota's Python generator let attacker-controlled enum value descriptions from x-ms-enum.values[].description flow through KiotaBuilder.SetEnumOptions into Documentation.DescriptionTemplate and PythonConventionService.RemoveInvalidDescriptionCharacters without newline sanitization, allowing generated inline comments to split and execute attacker-controlled Python code at module scope when generated modules were imported. This issue is fixed in version 1.32.0.

An input validation and injection vulnerability exists in Canonical ubuntu-pro-client (formerly ubuntu-advantage-tools). The client constructs APT source files (such as /etc/apt/sources.list.d/ubuntu-.list or their DEB822 equivalents) using data received directly from the contract server response via the directives.suites[] and directives.aptURL fields. Because the client utilizes Python's str.format() to write these files without performing escaping, validation, or newline character filtering, a malicious or tampered contract response containing embedded newline (\n) characters can successfully inject arbitrary, attacker-controlled deb configuration lines into root-owned APT sources. When combined with the unvalidated additionalPackages[] field—which is passed positionally into a root-executed apt-get install command—an attacker capable of spoofing or manipulating the contract response (e.g., via a compromised internal infrastructure, an intercepted connection utilizing a trusted CA, or local logical bugs) can force the client to fetch and install malicious packages. This ultimately leads to arbitrary code execution with root privileges on the affected system. This component is preinstalled on supported Ubuntu Server releases and auto-attaches by default on cloud provider Ubuntu Pro images.

Improper TLS hostname verification in Snowflake Connector for Python versions prior to 4.7.1 may have allowed a network-positioned attacker to bypass certificate hostname validation on HTTPS connections made by the connector. An attacker with on-path network access could exploit this by intercepting or redirecting network traffic and presenting a certificate signed by any trusted CA for any domain, causing the connector to accept connections without validating that the certificate matched the requested hostname. Successful exploitation requires an on-path traffic interception capability (e.g. ARP/DNS poisoning, rogue access point, BGP hijacking, or malicious proxy/exit node). This vulnerability may have exposed credentials, query data, and staged file contents to interception and tampering, and may have enabled the attacker to issue arbitrary SQL within the context of the victim's connector session. Impact is limited by the privileges of the affected Snowflake role. The fix is available in Snowflake Connector for Python version 4.7.1. Users must manually upgrade.

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.