langchain-ai/langchain: Exposure of Sensitive Information to an Unauthorized Actor
CVE-2025-6984 is a high-severity exposure of sensitive information to an unauthorized actor vulnerability in langchain-ai/langchain from LangChain AI, with a CVSS 3.0 base score of 7.5 out of 10. It can be exploited remotely over the network by an unauthenticated attacker, without any action from a user. Affected langchain-ai/langchain versions: latest and earlier. The record does not name a fixed version, so check the vendor advisory. There is no confirmed exploitation so far. EPSS estimates a 1.65% chance of exploitation within 30 days, higher than 77% of scored CVEs.
High severity with no evidence of exploitation so far.
What to do
- Check which version of langchain-ai/langchain you run against the affected versions below, and install the vendor's latest release.
- Until you can update, restrict network access to the affected service so it is not reachable from untrusted networks.
Affected products and versions
| Vendor | Product | Affected versions | Fixed in |
|---|---|---|---|
| Langchain-ai | langchain-ai/langchain | latest and earlier | Not stated |
Version data comes from the organisation that assigned the CVE. Confirm against the vendor advisory before deciding you are unaffected.
How the severity score breaks down
- Attack vector
- NetworkCan be exploited remotely over a network, including the internet.
- Attack complexity
- LowNo special conditions are needed; the attack works reliably.
- Privileges required
- NoneNo account or login is needed.
- User interaction
- NoneNo action by a victim is required.
- Scope
- UnchangedImpact stays within the vulnerable component.
- Confidentiality
- HighAll data handled by the component can be read.
- Integrity
- NoneNothing can be modified.
- Availability
- NoneAvailability is not affected.
Vector: CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N. Scored by CNA (huntr.dev).
Official description
The langchain-ai/langchain project, specifically the EverNoteLoader component, is vulnerable to XML External Entity (XXE) attacks due to insecure XML parsing. The affected version is 0.3.63. The vulnerability arises from the use of etree.iterparse() without disabling external entity references, which can lead to sensitive information disclosure. An attacker could exploit this by crafting a malicious XML payload that references local files, potentially exposing sensitive data such as /etc/passwd.
Source: the CVE record as published by its numbering authority, via NVD and CVE.org.
The underlying weakness: Exposure of Sensitive Information to an Unauthorized Actor
The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.
How developers prevent this class of flaw
- Compartmentalize the system to have safe areas where trust boundaries can be unambiguously drawn. Do not allow sensitive data to go outside of the trust boundary and always be careful when interfacing with a compartment outside of the safe area. Ensure that appropriate compartmentalization is built into the system design, and the compartmentalization allows for and reinforces privilege separation functionality. Architects and designers should rely on the principle of least privilege to decide the appropriate time to use privileges and the time to drop privileges.
More Exposure of Sensitive Information to an Unauthorized Actor vulnerabilities (CWE-200)
Timeline
- CVE record published.
- CISA published its SSVC assessment (exploitation: poc, automatable: no, technical impact: partial).
- Record last changed materially (score, affected products, status or references).
References
Other references
Other vulnerabilities in langchain-ai/langchain
- 7.3 High severity
- 7.5 High severity
- 10.0 Critical severity
- 9.8 Critical severity
- 7.8 High severity
- 7.7 High severity
Recent Exposure of Sensitive Information to an Unauthorized Actor vulnerabilities
- 9.9 Critical severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
- 7.5 High severity
Spotted an error? Tell us.