dependabot[bot]
8454542a34
Bumps [pyasn1](https://github.com/pyasn1/pyasn1) from 0.6.3 to 0.6.4. <details> <summary>Release notes</summary> <p><em>Sourced from <a href="https://github.com/pyasn1/pyasn1/releases">pyasn1's releases</a>.</em></p> <blockquote> <h2>Release 0.6.4</h2> <p>This is a security release.</p> <ul> <li>CVE-2026-59885 (GHSA-8ppf-4f7h-5ppj): Fixed quadratic time complexity in the OBJECT IDENTIFIER and RELATIVE-OID decoders. A small crafted substrate encoding many arcs could consume excessive CPU.</li> <li>CVE-2026-59884 (GHSA-m4p7-r5rc-7g4j): Limited BER long-form tag IDs to 20 octets (140 bits). Unbounded tag IDs allowed a crafted substrate to consume excessive CPU and memory.</li> <li>CVE-2026-59886 (GHSA-hm4w-wwcw-mr6r): Fixed excessive memory and CPU consumption in <code>Real.__float__()</code> for values with large base-10 exponents.</li> <li>Pinned PyPI publish GitHub Action to an immutable commit.</li> </ul> <p>All changes are noted in the <a href="https://github.com/pyasn1/pyasn1/blob/main/CHANGES.rst">CHANGELOG</a>.</p> </blockquote> </details> <details> <summary>Changelog</summary> <p><em>Sourced from <a href="https://github.com/pyasn1/pyasn1/blob/main/CHANGES.rst">pyasn1's changelog</a>.</em></p> <blockquote> <h2>Revision 0.6.4, released 08-07-2026</h2> <ul> <li>CVE-2026-59885 (GHSA-8ppf-4f7h-5ppj): Fixed quadratic time complexity in the OBJECT IDENTIFIER and RELATIVE-OID decoders. A small crafted substrate encoding many arcs could consume excessive CPU. Arcs are now accumulated in linear time; decoded values are unchanged (thanks for reporting, tynus2)</li> <li>CVE-2026-59884 (GHSA-m4p7-r5rc-7g4j): Limited BER long-form tag IDs to 20 octets (140 bits), matching the OID arc limit introduced in 0.6.2. Unbounded tag IDs allowed a crafted substrate to consume excessive CPU and memory; longer tag IDs are now rejected with PyAsn1Error. Also fixed Tag and TagSet repr() failing on huge tag (thanks for reporting, mikeappsec) IDs due to the integer-to-string conversion limit (Python 3.11+)</li> <li>CVE-2026-59886 (GHSA-hm4w-wwcw-mr6r): Fixed excessive memory and CPU consumption in Real.<strong>float</strong>() for values with large base-10 exponents. Conversion no longer materializes huge intermediate integers; values too large to represent as a Python float raise OverflowError promptly, and prettyPrint() renders them as '<!-- raw HTML omitted -->' as before. Also fixed base-10 mantissa normalization to use exact integer arithmetic; mantissas larger than 2**53 could previously lose precision through float division (thanks for reporting, gvozdila)</li> <li>Pinned PyPI publish GitHub Action to an immutable commit [pr <a href="https://redirect.github.com/pyasn1/pyasn1/issues/113">#113</a>](<a href="https://redirect.github.com/pyasn1/pyasn1/pull/113">pyasn1/pyasn1#113</a>)</li> </ul> </blockquote> </details> <details> <summary>Commits</summary> <ul> <li><a href="https://github.com/pyasn1/pyasn1/commit/72e4803405816c371ed3b2cb4be181c47f038406"><code>72e4803</code></a> Prepare release 0.6.4</li> <li><a href="https://github.com/pyasn1/pyasn1/commit/0c19eeb853731db1c717ff125ea001a1e558332d"><code>0c19eeb</code></a> Pin PyPI publish action to immutable commit (<a href="https://redirect.github.com/pyasn1/pyasn1/issues/113">#113</a>)</li> <li><a href="https://github.com/pyasn1/pyasn1/commit/45bdb19eb7df4b3780fe9c912c63e99bffc39dd9"><code>45bdb19</code></a> Merge commit from fork</li> <li><a href="https://github.com/pyasn1/pyasn1/commit/628e36ecbb5277a3f01572ce418ef54271b165a5"><code>628e36e</code></a> Merge commit from fork</li> <li><a href="https://github.com/pyasn1/pyasn1/commit/e60c691cb91addb8fcefa2f537e85ede6fb1e886"><code>e60c691</code></a> Merge commit from fork</li> <li>See full diff in <a href="https://github.com/pyasn1/pyasn1/compare/v0.6.3...v0.6.4">compare view</a></li> </ul> </details> <br /> [](https://docs.github.com/en/github/managing-security-vulnerabilities/about-dependabot-security-updates#about-compatibility-scores) Dependabot will resolve any conflicts with this PR as long as you don't alter it yourself. You can also trigger a rebase manually by commenting `@dependabot rebase`. [//]: # (dependabot-automerge-start) [//]: # (dependabot-automerge-end) --- <details> <summary>Dependabot commands and options</summary> <br /> You can trigger Dependabot actions by commenting on this PR: - `@dependabot rebase` will rebase this PR - `@dependabot recreate` will recreate this PR, overwriting any edits that have been made to it - `@dependabot show <dependency name> ignore conditions` will show all of the ignore conditions of the specified dependency - `@dependabot ignore this major version` will close this PR and stop Dependabot creating any more for this major version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this minor version` will close this PR and stop Dependabot creating any more for this minor version (unless you reopen the PR or upgrade to it yourself) - `@dependabot ignore this dependency` will close this PR and stop Dependabot creating any more for this dependency (unless you reopen the PR or upgrade to it yourself) You can disable automated security fix PRs for this repo from the [Security Alerts page](https://github.com/langchain-ai/langchain/network/alerts). </details> Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
🦜️🔗 LangChain
Looking for the JS/TS version? Check out LangChain.js.
To help you ship LangChain apps to production faster, check out LangSmith. LangSmith is a unified developer platform for building, testing, and monitoring LLM applications.
Quick Install
uv add langchain
🤔 What is this?
LangChain is the easiest way to start building agents and applications powered by LLMs. With under 10 lines of code, you can connect to OpenAI, Anthropic, Google, and more. LangChain provides a pre-built agent architecture and model integrations to help you get started quickly and seamlessly incorporate LLMs into your agents and applications.
We recommend you use LangChain if you want to quickly build agents and autonomous applications. Use LangGraph, our low-level agent orchestration framework and runtime, when you have more advanced needs that require a combination of deterministic and agentic workflows, heavy customization, and carefully controlled latency.
LangChain agents are built on top of LangGraph in order to provide durable execution, streaming, human-in-the-loop, persistence, and more. (You do not need to know LangGraph for basic LangChain agent usage.)
📖 Documentation
For full documentation, see the API reference. For conceptual guides, tutorials, and examples on using LangChain, see the LangChain Docs. You can also chat with the docs using Chat LangChain.
📕 Releases & Versioning
See our Releases and Versioning policies.
💁 Contributing
As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.
For detailed information on how to contribute, see the Contributing Guide.
Resources
- LangChain Academy — comprehensive, free courses on LangChain libraries and products, made by the LangChain team
- Code of Conduct — community guidelines and standards