VulnerabilityPublished 23 Apr 2026

CVE-2026-41182: langchain-ai langsmith-sdk · Information Exposure

Affects langchain-ai langsmith-sdkSource CVE Database V5

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Not known to be exploited · CVSS 5.3 Medium : upgrade to 0.7.31 or 0.5.19 when convenient.

Data as of 29 Oct 2026, 19:04 UTC

CVSS 3.1 base score

5.3Medium

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 0.2% chance of exploitation in 30 days – higher than 11% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 0.7.31, 0.5.19

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:N/A:N

Attack Vector: Network
Attack Complexity: Low
Privileges Required: None
User Interaction: None
Scope: Unchanged
Confidentiality: Low
Integrity: None
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Network: The vulnerable component is bound to the network stack and the set of possible attackers extends beyond the other options listed, up to and including the entire Internet. Such a vulnerability is often termed 'remotely exploitable' and can be thought of as an attack being exploitable at the protocol level one or more network hops away (e.g., across one or more routers).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: None: The attacker is unauthorized prior to attack, and therefore does not require any access to settings or files to carry out an attack.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Unchanged: An exploited vulnerability can only affect resources managed by the same security authority. In this case, the vulnerable component and the impacted component are either the same, or both are managed by the same security authority.
Confidentiality: Low: There is some loss of confidentiality. Access to some restricted information is obtained, but the attacker does not have control over what information is obtained, or the amount or kind of loss is limited. The information disclosure does not cause a direct, serious loss to the impacted component.
Integrity: None: There is no loss of integrity within the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 23 Apr 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 29 Oct 2026.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponized: A Metasploit exploit module or Exploit-DB entry exists (Metasploit scanner modules do not count), or CISA SSVC or the CVSS exploit maturity reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade langsmith-sdk to 0.7.31 or 0.5.19; langsmith-sdk to 0.7.31; langchain-ai/langsmith-sdk to 0.5.19.

Affected software

Product	Affected	Fixed in
langchain-ailangsmith-sdk	Affected <0.7.31	Fixed in 0.7.31
langchain-ailangsmith-sdk	Affected <0.5.19	Fixed in 0.5.19
npmlangchain-ai/langsmith-sdk`pkg:npm/langchain-ai/langsmith-sdk`Other threats	Affected <0.5.19	Fixed in 0.5.19
PyPIlangsmith-sdk`pkg:pypi/langsmith-sdk`Other threats	Affected <0.7.31	Fixed in 0.7.31

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

Upgrade to langsmith-sdk JavaScript version 0.5.19 or later and Python version 0.7.31 or later. These versions fix the issue by applying output redaction controls to streaming token events. No other mitigation is indicated or required.

Description

CVE-2026-41182 is a vulnerability in the langchain-ai langsmith-sdk JavaScript and Python SDKs prior to versions 0.5.19 and 0.7.31 respectively. The issue arises because output redaction controls do not apply to streaming token events, allowing raw token values from streaming LLM outputs to be recorded and stored without redaction. This results in unintended exposure of sensitive information through run event data. The vulnerability has a CVSS score of 5.3, indicating medium severity. Fixed versions are available that address this issue by properly applying redaction to streaming events.

Impact

Sensitive information generated by language model streaming outputs may be exposed to unauthorized actors because the redaction controls fail to sanitize streaming token events. This can lead to leakage of confidential or sensitive data stored within the LangSmith platform through run event logs. The vulnerability does not affect integrity or availability but impacts confidentiality.

Summary

The langsmith-sdk JavaScript and Python SDKs before versions 0.5.19 and 0.7.31 do not apply output redaction controls to streaming token events generated during LLM runs. Specifically, each chunk of streaming output is recorded as a new_token event containing the raw token value, which bypasses the redaction pipeline that only processes inputs and outputs fields. Consequently, sensitive streamed content can be leaked via run events despite redaction settings. The issue is fixed in versions 0.5.19 (JS) and 0.7.31 (Python).

CWE-200Exposure of Sensitive Information to an Unauthorized Actor (opens in a new tab)
Class weaknessLikelihood of exploit: HighCWE Top 25 (2025): #20OWASP Top 10 A01:2025: Broken Access Control (opens in a new tab)
The product exposes sensitive information to an actor that is not explicitly authorized to have access to that information.
MITRE discourages mapping vulnerabilities to this broad entry; the root cause is usually a more specific weakness.
Architecture and Design · Separation of Privilege
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.
OWASP Cheat Sheets
Error Handling (opens in a new tab)
Logging (opens in a new tab)
Authorization (opens in a new tab)
OWASP ASVS 4.0.3
V8.3.4 (opens in a new tab)
V14.3.3 (opens in a new tab)
V7.3.3 (opens in a new tab)
Attack patterns
Subverting Environment Variable Values (opens in a new tab)
ICMP Echo Request Ping (opens in a new tab)
TCP SYN Scan (opens in a new tab)
Enumerate Mail Exchange (MX) Records (opens in a new tab)
DNS Zone Transfers (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-359Exposure of Private Personal Information to an Unauthorized Actor (opens in a new tab)
Base weaknessOWASP Top 10 A01:2025: Broken Access Control (opens in a new tab)
The product does not properly prevent a person's private, personal information from being accessed by actors who either (1) are not explicitly authorized to access the information or (2) do not have the implicit consent of the person about whom the information is collected.
Requirements
Identify and consult all relevant regulations for personal privacy. An organization may be required to comply with certain federal and state regulations, depending on its location, the type of business it conducts, and the nature of any private data it handles.
Architecture and Design
Carefully evaluate how secure design may interfere with privacy, and vice versa. Security and privacy concerns often seem to compete with each other. From a security perspective, all important operations should be recorded so that any anomalous activity can later be identified.
Implementation · Operation · Attack Surface Reduction
Some tools can automatically analyze documents to redact, strip, or "sanitize" private information, although some human review might be necessary. Tools may vary in terms of which document formats can be processed.
OWASP Cheat Sheets
Error Handling (opens in a new tab)
Authorization (opens in a new tab)
OWASP ASVS 4.0.3
V10.2.1 (opens in a new tab)
V8.3.4 (opens in a new tab)
V14.3.3 (opens in a new tab)
Attack patterns
Evercookie (opens in a new tab)
Cross Site Identification (opens in a new tab)
Probe iOS Screenshots (opens in a new tab)
Shoulder Surfing (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).
CWE-532Insertion of Sensitive Information into Log File (opens in a new tab)
Base weaknessLikelihood of exploit: MediumOWASP Top 10 A09:2025: Security Logging & Alerting Failures (opens in a new tab)
The product writes sensitive information to a log file.
Architecture and Design · Implementation
Consider seriously the sensitivity of the information written into log files. Do not write secrets into the log files.
Distribution
Remove debug log files before deploying the application into production.
Operation
Protect log files against unauthorized read/write.
OWASP Cheat Sheets
Application Logging Vocabulary (opens in a new tab)
Logging (opens in a new tab)
OWASP ASVS 4.0.3
V7.1.1 (opens in a new tab)
V7.1.2 (opens in a new tab)
V8.3.5 (opens in a new tab)
Attack patterns
Fuzzing for application mapping (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

github.com/langchain-ai/langsmith-sdk/security/advisories/GHSA-rr7j-v2q5-chgv (opens in a new tab)

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 30 Apr 2026, 08:11 UTC

WeaknessesCWE-200, CWE-359, CWE-532

Technical details

References

Community reviews

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