Vulnerabilidades do Pip Praisonai

PraisonAI is a multi-agent teams system. From version 4.5.115 to before version 4.6.61, the published A2U advisory GHSA-f292-66h9-fpmf says unauthenticated A2U event streaming was fixed in praisonai 4.5.115. Current head still exposes the same A2U subscription and event routes without authentication when the operator starts the documented CLI entrypoint. The current CLI wrapper does not expose --api-key, does not install the common API-key middleware, and does not generate a token for A2U. It calls create_a2u_routes(app) directly. That helper only enforces auth if A2U_AUTH_TOKEN is already present; if the variable is missing, _authenticate_request() returns None and treats auth as disabled. This issue has been patched in version 4.6.61.

PraisonAI is a multi-agent teams system. From version 4.5.110 to before version 4.6.61, praisonai.sandbox.SandlockSandbox is documented and implemented as the kernel-enforced sandbox backend for untrusted code. Its SandboxConfig.native() path lets callers configure allowed filesystem paths and network=False. On systems where the optional sandlock module imports but reports that Landlock is unavailable, SandlockSandbox.execute() and run_command() do not fail closed. They silently fall back to SubprocessSandbox(self.config). That fallback keeps the same high-level native policy object but does not enforce the native filesystem or network boundary during code execution. A sandboxed payload can read files outside the configured allowed path and open network connections despite network=False. This issue has been patched in version 4.6.61.

PraisonAI is a multi-agent teams system. From version 4.5.87 to before version 4.6.61, PraisonAI recipe execution has a dangerous-tool policy that is supposed to block default-denied tools unless the caller explicitly passes allow_dangerous_tools=True. That policy only checks tools declared in TEMPLATE.yaml requires.tools. For steps-based recipes, the actual execution path loads workflow.yaml with YAMLWorkflowParser. That parser resolves agent-level tools: declarations and preserves top-level approve:. Workflow.start() then installs those YAML-approved tools into the approval context. As a result, an untrusted recipe can omit execute_command from TEMPLATE.yaml requires.tools, declare it in workflow.yaml agents.*.tools, and add top-level approve: [execute_command]. The caller did not set allow_dangerous_tools=True, but the recipe policy allows the recipe and the workflow approval path self-approves the critical shell tool. This issue has been patched in version 4.6.61.

PraisonAI is a multi-agent teams system. From version 4.5.126 to before version 4.6.59, PraisonAI's Async Jobs API validates webhook_url when a job request is parsed and again when the internal Job object is constructed. That validation blocks direct loopback/private targets, but it is not bound to the later network request. When a job completes, _send_webhook() passes the original hostname to httpx.AsyncClient.post() with no send-time validation, IP pinning, or guarded transport. An attacker-controlled hostname can therefore resolve to a public IP during Pydantic validation and later resolve to loopback/private/cloud-metadata infrastructure during webhook delivery. This bypasses the intended SSRF guard in current supported releases. This appears to be an incomplete fix / patch bypass for GHSA-8frj-8q3m-xhgm. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 2.6.0 to before version 4.6.59, PraisonAI's template loader accepts GitHub template URIs with refs, for example github:owner/repo/template@v1.0.0. The resolver stores the user-controlled template path and ref verbatim, and the cache layer later joins those values into ~/.praison/cache/templates/github/<owner>/<repo>/<template>/<ref> without normalizing each segment or checking that the final path remains inside the template cache root. A crafted ref such as ../../../../../../outside-delete-target therefore escapes the cache directory. The first load can write .cache_meta.json outside the cache. If the normal cache hierarchy for the same owner/repo/template has already been created, the same path reaches shutil.rmtree(cache_path) and removes an attacker-selected outside directory before replacing it with cache metadata. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 4.5.2 to before version 4.6.59, praisonai.bots.HTTPApproval renders pending tool approval arguments directly into the approval dashboard HTML. An attacker-controlled tool argument can inject JavaScript into that page. When a human opens the approval URL to inspect the risky tool request, the script runs in the dashboard origin and can POST to the same request's /approve/{request_id}/decide endpoint, causing HTTPApproval to return approved=True. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 4.5.87 to before version 4.6.59, PraisonAI recipe execution blocks default-denied dangerous tools unless the caller explicitly passes allow_dangerous_tools=True. The normal recipe.run() path enforces this with _check_tool_policy(). The streaming path, recipe.run_stream(), loads the same recipe, checks dependencies, and then calls _execute_recipe() without running the dangerous-tool policy check. As a result, a recipe that honestly declares execute_command in TEMPLATE.yaml requires.tools is denied by recipe.run(), but reaches the execution engine through recipe.run_stream() with allow_dangerous_tools=False. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 4.6.56 to before version 4.6.59, PraisonAI's LinearBot starts a public webhook listener on 0.0.0.0 and treats LINEAR_WEBHOOK_SECRET as optional. When the secret is absent, startup only logs a warning and _handle_webhook() skips Linear-Signature verification entirely. An unauthenticated network caller who can reach the webhook endpoint can submit a forged Linear-Event: AgentSession request. The forged request is parsed, scheduled for background processing, dispatched to _handle_agent_session(), and passed into BotSessionManager.chat(). The bot then attempts to post the agent response back to Linear under the configured bot token. The PoV is offline and deterministic. It does not contact Linear. It calls the webhook handler directly, monkey-patches the outbound Linear comment path, and proves both sides of the boundary. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 4.5.112 to before version 4.6.59, PraisonAI's installed console entrypoint is Typer-first. In current releases, the recipe command is registered in the Typer app and praisonai recipe serve dispatches to the deprecated Typer command in src/praisonai/praisonai/cli/commands/recipe.py. That Typer command can start the Recipe HTTP server on a non-localhost interface with no authentication. It prints a deprecation warning, and then launches the server. Because config.auth is absent, create_app() does not attach the API-key or JWT middleware. Unauthenticated requests can then reach the recipe API and, when enabled, /admin/reload. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 3.11.0 to before version 4.6.59, PraisonAI's Slack bot applies its configured allowed_users, allowed_channels, and unknown-user pairing policy in the normal Slack message event handler, but not in the adjacent Slack app_mention event handler. A Slack workspace user who can mention the bot in a channel where the Slack app is present can trigger the configured PraisonAI agent even when: the sender is not in BotConfig.allowed_users; the channel is not in BotConfig.allowed_channels; unknown_user_policy="deny" is configured; and the same event content is correctly dropped by the normal message handler. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 3.8.1 to before version 4.6.59, PraisonAI's Dynamic Context Discovery feature exposes artifact helper tools through ctx.get_tools(). The implemented artifact tools do not enforce that the supplied artifact_path is an artifact created by the configured store or that it lives under the configured artifact base directory. Instead, artifact_head, artifact_tail, artifact_grep, and artifact_chunk wrap the caller-supplied path directly into an ArtifactRef and then read it from the host filesystem. As a result, any prompt/user/tool-caller that can influence those tool arguments can read files readable by the PraisonAI process, such as project .env files, cloud credentials, SSH keys, source files, or other local data. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 3.8.1 to before version 4.6.59, PraisonAI's Dynamic Context module provides filesystem-backed history and terminal-log storage. The module also exports agent-callable tool factories. Those tools accept run_id and agent_id arguments from the tool caller. The underlying stores join those values into filesystem paths without rejecting absolute paths or .. traversal. Because run_id can be an absolute path and agent_id can contain traversal, a lower-trust prompt/user that can call these tools can read .jsonl and .log files outside the configured Dynamic Context base directory. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. From version 4.5.2 to before version 4.6.59, praisonai.bots.DiscordApproval approves a pending dangerous tool call when it sees any later non-bot message in the configured Discord channel whose text is classified as approval, such as yes. As a result, any user who can post in the configured approval channel can approve a pending high-risk tool call by sending yes after the approval message appears. the same PoV also shows that the Slack and Telegram messaging approval backends have no explicit approver allowlist parameter, but the primary report-grade issue is the Discord backend's unthreaded channel cross-talk: the approving message does not need to be a reply or otherwise request-bound. This issue has been patched in version 4.6.59.

PraisonAI is a multi-agent teams system. In versions 3.9.26 through 4.6.57 of praiseonai and 0.12.12 through 1.6.57 of praiseonaiagents, the workflow "include" feature is vulnerable to code execution. Workflow._execute_include() implicitly imports and runs an included recipe's tools.py via a raw importlib.util.spec_from_file_location() and spec.loader.exec_module() call, without honoring the PRAISONAI_ALLOW_TEMPLATE_TOOLS/PRAISONAI_ALLOW_LOCAL_TOOLS autoload opt-in gates or routing through the centralized safe loader that protects the other tools.py autoload paths. As a result, a workflow that includes an attacker-controlled local recipe directory executes arbitrary module-level Python code during include setup, before any child workflow parsing or model call, and the same sink is reachable through the higher-level praisonai.recipe.run() recipe API. An attacker who can cause a victim process to run a workflow or recipe that includes an untrusted local recipe achieves arbitrary Python code execution as the PraisonAI process user, a variant that bypasses the hardening applied to the previously disclosed automatic tools.py RCE advisory family. This issue has been fixed in version 4.6.58 of praisonai and 1.6.58 of praisonaiagents.

PraisonAI is a multi-agent teams system. The v4.6.32 chokepoint refactor (which patched CVE-2026-44334 / GHSA-xcmw-grxf-wjhj) added the PRAISONAI_ALLOW_LOCAL_TOOLS env-var gate to the tool_override.py sinks. However, two additional spec.loader.exec_module call sites in praisonai/agents_generator.py were missed and remain completely unguarded in versions prior to 4.6.40. Both functions accept a module_path parameter sourced from YAML configuration and execute it without validation, signature checking, or the env-var gate. Version 4.6.40 fixes the issue.

PraisonAI is a multi-agent teams system. Prior to version 4.6.40, the fix for GHSA-9mqq-jqxf-grvw / CVE-2026-44336 is incomplete. The original advisory description named four vulnerable handlers in `mcp_server/adapters/cli_tools.py`. Commit `68cc9427` ("fix(security): harden MCP rules path handling…") added a `_resolve_rule_path()` helper and applied it to `rules.create`, `rules.show`, and `rules.delete`. `workflow.show` was left unchanged. Two adjacent handlers in the same file have the same pattern, `workflow.validate` and `deploy.validate`. Neither was mentioned in the original advisory. Both remained unchanged. The original advisory also identified the dispatcher (`server.py:281-298`) as a root cause. It accepts unvalidated `**kwargs` from `params["arguments"]` with no enforcement against the tool's declared `input_schema`. That code is unchanged prior to version 4.6.40. A single unauthenticated MCP `tools/call` to `praisonai.workflow.show` returns the contents of any file the host user can read: `/etc/passwd`, `~/.ssh/id_rsa`, `~/.aws/credentials`, or any project `.env`. Version 4.6.40 contains an updated fix.

PraisonAI before 4.6.78 fails to verify Svix webhook signatures in AgentMail webhook mode, allowing unauthenticated attackers to forge message.received events. Attackers can send crafted JSON payloads to the webhook endpoint to invoke configured agents with arbitrary sender addresses and message content.

PraisonAI before 4.6.78 contains an authentication bypass in the Call API agent invocation endpoints (src/praisonai/praisonai/api/agent_invoke.py) when PRAISONAI_CALL_AUTH=disabled is configured. The safeguard intended to restrict the disabled-auth opt-out to localhost binding derives the bind host from request.url.hostname, which is taken from the client-controlled HTTP Host header. A remote, unauthenticated attacker who can reach the service over the network can send a spoofed 'Host: 127.0.0.1' header to bypass the localhost-only restriction and list (GET /api/v1/agents) and invoke (POST /api/v1/agents/{agent_id}/invoke) registered agents without authentication.

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.

PraisonAI before 4.6.78 exposes the MCP HTTP-stream transport without authentication by default: the CLI --api-key option defaults to None, and the server only enforces Authorization/Bearer checks when an API key is configured. When an operator runs 'praisonai mcp serve --transport http-stream' without an API key, an unauthenticated client (no Authorization header, and no Origin header, which is also permitted) can initialize a session, enumerate the available tools (tools/list), and invoke tools (tools/call). Additionally, the dispatcher forwards tool-call arguments to handlers without validating them against the advertised inputSchema. The server binds to 127.0.0.1 by default, so remote exploitation requires the operator to bind to a network-accessible address (e.g., --host 0.0.0.0).

PraisonAI before 4.6.78 contains an unenforced security policy vulnerability in the default Subprocess Sandbox backend where blocked_commands, blocked_paths, blocked_imports, allow_subprocess, and allow_file_write restrictions are completely ignored. Attackers can execute arbitrary subprocess commands, read sensitive files, and perform destructive operations despite explicit security policy configuration.