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2.1
CVE-2026-7700: Langflow Smart Transform can run attacker code
CVE-2026-7700 · published 3 days ago
Summary
Versions of Langflow from 1.3.0 to 1.10.2 let a specially crafted prompt create and run arbitrary Python code. An attacker who can control the instructions or input passed to the Smart Transform component could execute commands on the server hosting Langflow. Update to a patched version or restrict who can edit flows and what inputs reach this component.
What to do
- Update langflow to version 1.10.3.
Affected software
| Ecosystem | Vendor | Product | Affected versions |
|---|---|---|---|
| pip | – | langflow |
>= 1.3.0, < 1.10.3 Fix: upgrade to 1.10.3
|
| – | langflow-ai | langflow | 1.10.0 |
Original advisory text
Langflow: Prompt injection in Langflow Smart Transform can lead to code execution
## Summary
Langflow versions 1.3.0 through 1.10.2 contain a code-injection vulnerability in the Smart Transform (`LambdaFilterComponent`) component.
Smart Transform places flow-author instructions and a preview of its input data into a prompt asking an LLM to generate a Python lambda. It then extracts a one-line lambda from the model response, applies only syntactic format checks, evaluates it with Python's full builtins, and invokes the resulting function inside the Langflow process.
A malicious flow author can exploit this directly through the Instructions field. In deployments where an exposed flow passes attacker-controlled content into Smart Transform, an attacker may also exploit it indirectly through prompt injection, subject to the configured model following the injected instruction.
## Vulnerability details
**Vulnerable Code Location**: `src/lfx/src/lfx/components/llm_operations/lambda_filter.py` (line 242 in v1.10.2)
```python
def _validate_lambda(self, lambda_text: str) -> bool:
"""Validate the provided lambda function text."""
return lambda_text.strip().startswith("lambda") and ":" in lambda_text
# ...
return eval(lambda_text) # noqa: S307
```
For example, an attacker can attempt to make the model return:
`lambda x: __import__("os").system("id")`
This expression satisfies the vulnerable format checks. `eval()` creates the lambda with access to Python's default builtins, and the subsequent `fn(data)` invocation (in `_execute_lambda`) executes the command.
Successful exploitation allows code execution with the privileges of the Langflow service process. This can expose or modify credentials, files, application data, and network resources accessible to that process, and may affect other tenants in shared deployments.
## PoC
https://github.com/user-attachments/assets/13c48fe1-7225-4e0d-9687-2d2df1e87f0e
## Fix
The reported path was addressed by validating the generated code's AST and evaluating it with a restricted builtins mapping.
The mainline fix is in PR #13530 (`1641b28f`) and shipped in Langflow 1.11.0. The 1.10.3 backport is in PR #14071 (`94859df3`). Users should upgrade to Langflow 1.10.3 or later.
## Workarounds
Until an upgrade is possible:
- Remove Smart Transform from runnable flows.
- Restrict flow creation, editing, and execution to trusted users.
- Do not route untrusted or externally controlled data through Smart Transform.
- Limit the Langflow process's filesystem, network, and credential access.
## Credit
- **Peyton Kennedy ([p80n-sec](https://github.com/p80n-sec)) of Endor Labs** — reporter (original finder)
- **[SZXSec](https://github.com/SZXSec)** — reporter (duplicate report)
- **[cyjhhh](https://github.com/cyjhhh)** — reporter (duplicate report)
- **[0gur1](https://github.com/0gur1)** — reporter (duplicate report)
- **[ajm4n](https://github.com/ajm4n)** — reporter (duplicate report, Finding 1 of a multi-finding submission)
- **[andifilhohub](https://github.com/andifilhohub)** — analyst
- **Jordan Frazier ([jordanrfrazier](https://github.com/jordanrfrazier))** — remediation developer
Langflow versions 1.3.0 through 1.10.2 contain a code-injection vulnerability in the Smart Transform (`LambdaFilterComponent`) component.
Smart Transform places flow-author instructions and a preview of its input data into a prompt asking an LLM to generate a Python lambda. It then extracts a one-line lambda from the model response, applies only syntactic format checks, evaluates it with Python's full builtins, and invokes the resulting function inside the Langflow process.
A malicious flow author can exploit this directly through the Instructions field. In deployments where an exposed flow passes attacker-controlled content into Smart Transform, an attacker may also exploit it indirectly through prompt injection, subject to the configured model following the injected instruction.
## Vulnerability details
**Vulnerable Code Location**: `src/lfx/src/lfx/components/llm_operations/lambda_filter.py` (line 242 in v1.10.2)
```python
def _validate_lambda(self, lambda_text: str) -> bool:
"""Validate the provided lambda function text."""
return lambda_text.strip().startswith("lambda") and ":" in lambda_text
# ...
return eval(lambda_text) # noqa: S307
```
For example, an attacker can attempt to make the model return:
`lambda x: __import__("os").system("id")`
This expression satisfies the vulnerable format checks. `eval()` creates the lambda with access to Python's default builtins, and the subsequent `fn(data)` invocation (in `_execute_lambda`) executes the command.
Successful exploitation allows code execution with the privileges of the Langflow service process. This can expose or modify credentials, files, application data, and network resources accessible to that process, and may affect other tenants in shared deployments.
## PoC
https://github.com/user-attachments/assets/13c48fe1-7225-4e0d-9687-2d2df1e87f0e
## Fix
The reported path was addressed by validating the generated code's AST and evaluating it with a restricted builtins mapping.
The mainline fix is in PR #13530 (`1641b28f`) and shipped in Langflow 1.11.0. The 1.10.3 backport is in PR #14071 (`94859df3`). Users should upgrade to Langflow 1.10.3 or later.
## Workarounds
Until an upgrade is possible:
- Remove Smart Transform from runnable flows.
- Restrict flow creation, editing, and execution to trusted users.
- Do not route untrusted or externally controlled data through Smart Transform.
- Limit the Langflow process's filesystem, network, and credential access.
## Credit
- **Peyton Kennedy ([p80n-sec](https://github.com/p80n-sec)) of Endor Labs** — reporter (original finder)
- **[SZXSec](https://github.com/SZXSec)** — reporter (duplicate report)
- **[cyjhhh](https://github.com/cyjhhh)** — reporter (duplicate report)
- **[0gur1](https://github.com/0gur1)** — reporter (duplicate report)
- **[ajm4n](https://github.com/ajm4n)** — reporter (duplicate report, Finding 1 of a multi-finding submission)
- **[andifilhohub](https://github.com/andifilhohub)** — analyst
- **Jordan Frazier ([jordanrfrazier](https://github.com/jordanrfrazier))** — remediation developer
References
- https://vuldb.com/submit/804305 URL
- https://vuldb.com/vuln/360869/cti
- https://vuldb.com/vuln/360869 URL
- https://www.yuque.com/mengnanbulalei/ognlsk/hte2a98ro5gf8tp9?singleDoc#%20%E3%80... URL
- https://github.com/langflow-ai/langflow Product
- https://github.com/langflow-ai/langflow/
- https://pypi.org/project/langflow Product
- https://github.com/advisories/GHSA-9fpm-3445-2vx4 Vendor Advisory
- https://github.com/langflow-ai/langflow/security/advisories/GHSA-9fpm-3445-2vx4 URL
- https://nvd.nist.gov/vuln/detail/CVE-2026-7700 Vendor Advisory
- https://github.com/langflow-ai/langflow/pull/13530 URL
- https://github.com/langflow-ai/langflow/commit/1641b28f33e2c47b9a0c6855922d44d1b... URL
- https://github.com/langflow-ai/langflow/commit/94859df33acd70b2a1f816e26d68f5e89... URL
- https://github.com/langflow-ai/langflow/releases/tag/v1.10.3 URL
- https://github.com/CVEProject/cvelistV5/tree/main/cves/2026/7xxx/CVE-2026-7700.j... Vendor Advisory
- https://vuldb.com/cve/CVE-2026-7700
Internet-facing
60 days
Internal
At next upgrade
- Not known to be exploited
- Needs hands-on effort to exploit
- Gives an attacker partial control
Type
CWE-74Injection
CWE-94Code Injection
Timeline
Published15 Oct 2026
Updated15 Oct 2026
First seen3 May 2026
Sources
CVE-2026-7700 · NVD
GHSA-9fpm-3445-2vx4 · GHSA
CVE-2026-7700 · MITRE
CVE-2026-7700 · OSV
GHSA-9fpm-3445-2vx4 · OSV
PYSEC-2026-4232 · OSV
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