Focus on langchain vulnerabilities and metrics.
Last updated: 16 Apr 2025, 22:25 UTC
This page consolidates all known Common Vulnerabilities and Exposures (CVEs) associated with langchain. We track both calendar-based metrics (using fixed periods) and rolling metrics (using gliding windows) to give you a comprehensive view of security trends and risk evolution. Use these insights to assess risk and plan your patching strategy.
For a broader perspective on cybersecurity threats, explore the comprehensive list of CVEs by vendor and product. Stay updated on critical vulnerabilities affecting major software and hardware providers.
Total langchain CVEs: 22
Earliest CVE date: 05 Apr 2023, 02:15 UTC
Latest CVE date: 29 Oct 2024, 13:15 UTC
Latest CVE reference: CVE-2024-8309
30-day Count (Rolling): 0
365-day Count (Rolling): 5
Calendar-based Variation
Calendar-based Variation compares a fixed calendar period (e.g., this month versus the same month last year), while Rolling Growth Rate uses a continuous window (e.g., last 30 days versus the previous 30 days) to capture trends independent of calendar boundaries.
Month Variation (Calendar): 0%
Year Variation (Calendar): -68.75%
Month Growth Rate (30-day Rolling): 0.0%
Year Growth Rate (365-day Rolling): -68.75%
Average CVSS: 0.0
Max CVSS: 0
Critical CVEs (≥9): 0
| Range | Count |
|---|---|
| 0.0-3.9 | 22 |
| 4.0-6.9 | 0 |
| 7.0-8.9 | 0 |
| 9.0-10.0 | 0 |
These are the five CVEs with the highest CVSS scores for langchain, sorted by severity first and recency.
A vulnerability in the GraphCypherQAChain class of langchain-ai/langchain version 0.2.5 allows for SQL injection through prompt injection. This vulnerability can lead to unauthorized data manipulation, data exfiltration, denial of service (DoS) by deleting all data, breaches in multi-tenant security environments, and data integrity issues. Attackers can create, update, or delete nodes and relationships without proper authorization, extract sensitive data, disrupt services, access data across different tenants, and compromise the integrity of the database.
A path traversal vulnerability exists in the `getFullPath` method of langchain-ai/langchainjs version 0.2.5. This vulnerability allows attackers to save files anywhere in the filesystem, overwrite existing text files, read `.txt` files, and delete files. The vulnerability is exploited through the `setFileContent`, `getParsedFile`, and `mdelete` methods, which do not properly sanitize user input.
A vulnerability in the GraphCypherQAChain class of langchain-ai/langchainjs versions 0.2.5 and all versions with this class allows for prompt injection, leading to SQL injection. This vulnerability permits unauthorized data manipulation, data exfiltration, denial of service (DoS) by deleting all data, breaches in multi-tenant security environments, and data integrity issues. Attackers can create, update, or delete nodes and relationships without proper authorization, extract sensitive data, disrupt services, access data across different tenants, and compromise the integrity of the database.
A Server-Side Request Forgery (SSRF) vulnerability exists in the Web Research Retriever component of langchain-ai/langchain version 0.1.5. The vulnerability arises because the Web Research Retriever does not restrict requests to remote internet addresses, allowing it to reach local addresses. This flaw enables attackers to execute port scans, access local services, and in some scenarios, read instance metadata from cloud environments. The vulnerability is particularly concerning as it can be exploited to abuse the Web Explorer server as a proxy for web attacks on third parties and interact with servers in the local network, including reading their response data. This could potentially lead to arbitrary code execution, depending on the nature of the local services. The vulnerability is limited to GET requests, as POST requests are not possible, but the impact on confidentiality, integrity, and availability is significant due to the potential for stolen credentials and state-changing interactions with internal APIs.
A Denial-of-Service (DoS) vulnerability exists in the `SitemapLoader` class of the `langchain-ai/langchain` repository, affecting all versions. The `parse_sitemap` method, responsible for parsing sitemaps and extracting URLs, lacks a mechanism to prevent infinite recursion when a sitemap URL refers to the current sitemap itself. This oversight allows for the possibility of an infinite loop, leading to a crash by exceeding the maximum recursion depth in Python. This vulnerability can be exploited to occupy server socket/port resources and crash the Python process, impacting the availability of services relying on this functionality.
LangChain through 0.1.10 allows ../ directory traversal by an actor who is able to control the final part of the path parameter in a load_chain call. This bypasses the intended behavior of loading configurations only from the hwchase17/langchain-hub GitHub repository. The outcome can be disclosure of an API key for a large language model online service, or remote code execution. (A patch is available as of release 0.1.29 of langchain-core.)
With the following crawler configuration: ```python from bs4 import BeautifulSoup as Soup url = "https://example.com" loader = RecursiveUrlLoader( url=url, max_depth=2, extractor=lambda x: Soup(x, "html.parser").text ) docs = loader.load() ``` An attacker in control of the contents of `https://example.com` could place a malicious HTML file in there with links like "https://example.completely.different/my_file.html" and the crawler would proceed to download that file as well even though `prevent_outside=True`. https://github.com/langchain-ai/langchain/blob/bf0b3cc0b5ade1fb95a5b1b6fa260e99064c2e22/libs/community/langchain_community/document_loaders/recursive_url_loader.py#L51-L51 Resolved in https://github.com/langchain-ai/langchain/pull/15559
In Langchain through 0.0.155, prompt injection allows an attacker to force the service to retrieve data from an arbitrary URL, essentially providing SSRF and potentially injecting content into downstream tasks.
LangChain before 0.0.317 allows SSRF via document_loaders/recursive_url_loader.py because crawling can proceed from an external server to an internal server.
langchain_experimental (aka LangChain Experimental) in LangChain before 0.0.306 allows an attacker to bypass the CVE-2023-36258 fix and execute arbitrary code via __import__ in Python code, which is not prohibited by pal_chain/base.py.
An issue in LanChain-ai Langchain v.0.0.245 allows a remote attacker to execute arbitrary code via the evaluate function in the numexpr library.
An issue in langchain v.0.0.171 allows a remote attacker to execute arbitrary code via a JSON file to load_prompt. This is related to __subclasses__ or a template.
An issue in langchain langchain-ai v.0.0.232 and before allows a remote attacker to execute arbitrary code via a crafted script to the PythonAstREPLTool._run component.
An issue in Harrison Chase langchain v.0.0.194 and before allows a remote attacker to execute arbitrary code via the from_math_prompt and from_colored_object_prompt functions.
An issue in LangChain v.0.0.231 allows a remote attacker to execute arbitrary code via the prompt parameter.
An issue in Harrison Chase langchain v.0.0.194 allows an attacker to execute arbitrary code via the python exec calls in the PALChain, affected functions include from_math_prompt and from_colored_object_prompt.
SQL injection vulnerability in langchain before v0.0.247 allows a remote attacker to obtain sensitive information via the SQLDatabaseChain component.
An issue in langchain v.0.0.64 allows a remote attacker to execute arbitrary code via the PALChain parameter in the Python exec method.
An issue in LangChain before 0.0.236 allows an attacker to execute arbitrary code because Python code with os.system, exec, or eval can be used.
Langchain 0.0.171 is vulnerable to Arbitrary code execution in load_prompt.
Langchain before v0.0.225 was discovered to contain a remote code execution (RCE) vulnerability in the component JiraAPIWrapper (aka the JIRA API wrapper). This vulnerability allows attackers to execute arbitrary code via crafted input. As noted in the "releases/tag" reference, a fix is available.
In LangChain through 0.0.131, the LLMMathChain chain allows prompt injection attacks that can execute arbitrary code via the Python exec method.