• 'Each vulnerability exposes a different class of enterprise data'

    From TechnologyDaily@1337:1/100 to All on Friday, March 27, 2026 17:15:30
    'Each vulnerability exposes a different class of enterprise data': LangChain framework hit by several worrying security issues here's what we know

    Date:
    Fri, 27 Mar 2026 17:10:00 +0000

    Description:
    LangChain and LangGraph have patched three high-severity and critical bugs.

    FULL STORY ======================================================================Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Tech Radar Pro Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Become a Member in Seconds Unlock instant access to exclusive member features. Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners or sponsors By submitting your information you agree to the Terms & Conditions and Privacy Policy and are aged 16 or over. You are
    now subscribed Your newsletter sign-up was successful Join the club Get full access to premium articles, exclusive features and a growing list of member rewards. Explore An account already exists for this email address, please log in. Subscribe to our newsletter LangChain and LangGraph patch three high-severity flaws exposing files, secrets, and conversation histories Vulnerabilities included path traversal, deserialization leaks, and SQL injection in SQLite checkpoints Researchers warn risks ripple through downstream libraries; developers urged to audit configs and treat LLM outputs as untrusted input LangChain and LangGraph, two popular open source
    frameworks for building AI apps, contained high-severity and critical vulnerabilities which allowed threat actors to exfiltrate sensitive data from compromised systems.

    LangChain helps developers build apps using large language models (LLM), by connecting AI models to various data sources and tools. It is a popular tool among developers looking to build chatbots and assistants. LangGraph, on the other hand, is built on top of LangChain and is designed to help create AI agents that follow structured, step-by-step workflows. It uses graphs to control how tasks move between steps, and devs use it for complex, multi-step processes. Citing stats on the Python Package Index (PyPI), The Hacker News says the projects have more than 60 million combined downloads a week, suggesting they are immensely popular in the software development community. Article continues below You may like Top LLM PyPl package compromised to
    steal user details - here's what we know Anthropic's official Git MCP server had some worrying security flaws - this is what happened next Python
    libraries used in top AI and ML tools hacked - Nvidia, Salesforce and other libraries all at risk Vulnerabilities and patches In total, the projects
    fixed three vulnerabilities:

    CVE-2026-34070 (severity score 7.5/10 - high) - A path traversal bug in LangChain that enables arbitrary file access without validation

    CVE-2025-68664 (severity score 9.3/10 - critical ) - A deserialization of untrusted data flaw in LangChain that leaks API keys and environment secrets

    CVE-2025-67644 (severity score 7.3/10 - high ) - An SQL injection vulnerability in LangGraph SQLite checkpoint implementation that enables SQL query manipulation Are you a pro? Subscribe to our newsletter Sign up to the TechRadar Pro newsletter to get all the top news, opinion, features and guidance your business needs to succeed! Contact me with news and offers from other Future brands Receive email from us on behalf of our trusted partners
    or sponsors By submitting your information you agree to the Terms &
    Conditions and Privacy Policy and are aged 16 or over.

    "Each vulnerability exposes a different class of enterprise data: filesystem files, environment secrets, and conversation history," security researcher Vladimir Tokarev of Cyera said in a report detailing the flaws.

    The Hacker News notes exploiting any of the three flaws allows threat actors to read sensitive files like Docker configurations, exfiltrate secrets
    through prompt injection, and even access conversation histories associated with sensitive workflows.

    All bugs have since been fixed so if youre using any of these tools, make
    sure to upgrade to the latest version to safeguard your projects. What to
    read next Security experts flag multiple issues in Claude Code, warning, 'As AI integration deepens, security controls must evolve to match the new trust boundaries' This 'ZombieAgent' zero click vulnerability allows for silent account takeover - here's what we know This WebUI vulnerability allows remote code execution - here's how to stay safe

    CVE-2026-34070 can be fixed by bringing langchain-core at least to version 1.2.22

    CVE-2025-68664 can be fixed by bringing langchain-core to versions n0.3.81 and 1.2.5

    CVE-2025-67644 can be fixed by bringing langgraph-checkpoint-sqlite to version 3.0.1 Foundational plumbing What is the biggest threat to enterprise AI data? (Image credit: Shutterstock / carlos castilla) For Cyera, the findings show that the biggest threat to enterprise AI data might not be as complex as people think.

    In fact, it hides in the invisible, foundational plumbing that connects your AI to your business. This layer is vulnerable to some of the oldest tricks in the hacker playbook, they said.

    They also warned that LangChain does not exist in isolation but rather sits
    at the center of a massive dependency web that stretches across the AI stack. WIth hundreds of libraries wrapping LangChain, extending it, or depending on it, it means that any vulnerability in the project also means vulnerabilities down the stream.

    The bugs ripple outward through every downstream library, every wrapper,
    every integration that inherits the vulnerable code path.

    In order to truly secure your environment, patching the tools will not suffice, they said. Any code that passes external or user-controlled configurations to load_prompt_from_config() or load_prompt() need to be audited, and developers should not enable secrets_from_env=True when deserializing untrusted data. The new default is False. Keep it that way,
    they warned.

    They also urged the community to treat LLM outputs as untrusted input, since different fields can be influenced by prompt injection. Finally, metadata filter keeys must be validated before they can be passed onto checkpoint queries.

    Never allow user-controlled strings to become dictionary keys in filter operations. The best antivirus for all budgets Our top picks, based on real-world testing and comparisons

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    Link to news story: https://www.techradar.com/pro/security/each-vulnerability-exposes-a-different- class-of-enterprise-data-langchain-framework-hit-by-several-worrying-security- issues-heres-what-we-know


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