Is langchain-openai safe?
What langchain-openai does
langchain-openai is the LangChain integration package for OpenAI. It lets LangChain applications call OpenAI models through the openai SDK. Its PyPI project links point to the langchain-ai/langchain repository, and the package is MIT licensed. It sends prompts and data to the OpenAI API, and the LangChain docs have you provide your key in the OPENAI_API_KEY environment variable. Before installing, create a dedicated OpenAI API key for the application so you can track and revoke it separately, and pin the package version.
- Python network egress
- Python filesystem read
- Delegated authentication (OAuth 2.0 / OIDC)
What to do: Nothing here argues against installing it. Grant the capabilities it lists only if you expect the tool to need them.
langchain-openai is a PyPI package analyzed by SkillTotal's deterministic static scanner. The scan found no malicious indicators. It can: delegated authentication, filesystem read, network egress and scoped identity — capabilities are what the code can do, not a verdict on intent. Risk score 0/100 (low).
langchain-openai 1.8.0
Get notified when this component changes
Change alerts aren't live yet. Leave your email and we'll let you know when they launch. We use it only for this and delete it on request.
Automated static-analysis result. It can contain false positives and false negatives, and is not a claim about the intent of langchain-openai's authors. Report a false positive.
Behavioral traits
How this component maps to the CSA agentic threat model. Descriptive — it never affects the risk score.
Findings (4)
The component reads files from disk.
raw_text = self.path.read_text(encoding="utf-8")
Why it matters: Usually legitimate, but worth confirming it can't be steered into reading sensitive files.
Fix: Confirm which files are read and that paths cannot be influenced by untrusted input to reach sensitive locations.
The component makes outbound network requests.
import httpx
import httpx
import urllib.request
return bool(urllib.request.getproxies())
detected = bool(urllib.request.getproxies())
import httpx
import httpx
import httpx
with httpx.Client(timeout=timeout) as client:
with httpx.Client(timeout=timeout) as client:
Why it matters: Usually legitimate, but confirm the destinations are expected and no sensitive data leaves.
Fix: Confirm the destination hosts are expected and that no sensitive data is sent off-host.
An OAuth 2.0 / OpenID Connect delegated-authentication flow was detected (authorization-code / refresh-token / token-exchange grant, an OIDC authorize/discovery endpoint or id_token, or a delegation library). Tools authenticate with the end user's delegated, scoped credentials rather than a long-lived embedded service credential. (17 occurrence(s) shown as evidence).
CHATGPT_AUTHORIZE_URL = "https://auth.openai.com/oauth/authorize"
`plan_type`, `user_id`) are populated when decodable from the `id_token`;
`id_token` itself is the raw token, not derived from it. Secret-bearing
fields (`access_token`, `refresh_token`, `id_token`) are excluded from the
id_token: str | None = field(default=None, repr=False)
def _extract_chatgpt_claims(id_token: str | None) -> dict[str, str | None]:
if not id_token:
claims = decode_jwt_claims(id_token)
"id_token; the `ChatGPT-Account-Id` header will be omitted."
id_token = payload.get("id_token")claims = _extract_chatgpt_claims(id_token)
id_token=id_token,
"id_token": token.id_token,
id_token=data.get("id_token"),"grant_type": "refresh_token",
"grant_type": "authorization_code",
"grant_type": "authorization_code",
Fix: Delegated auth is a lower-blast-radius execution context than an embedded static credential. Confirm the requested scopes are minimal and that tokens are never logged or forwarded off-host.
A short-lived, scoped, assumed identity was detected - an STS AssumeRole / session token, a cloud managed or workload identity, an impersonated service account, a projected Kubernetes service-account token, or a dynamic-secret broker. Tools authenticate with a narrowly-scoped credential that expires, rather than a long-lived embedded service credential. (2 occurrence(s) shown as evidence).
azure_identity.WorkloadIdentityCredential(),
azure_identity_aio.WorkloadIdentityCredential(),
Fix: A scoped, short-lived identity is the smallest-blast-radius execution context. Confirm the assumed role / requested scope grants only the permissions the tool needs, and that the token lifetime is minimal.
Maintain langchain-openai?
The free Claude Code plugin scans each npm, PyPI or MCP package with this report's open-source engine before the install command runs. It runs on your machine and needs no account.
Check your own component
Run the same evidence-backed scan on any MCP server, agent skill, or package.
Scan your own componentHow we determine this: deterministic static analysis (regex + AST), evidence-anchored, no code execution. Methodology →