CVE-2025-68664 Security Incident affecting AI
Evidence indicates that the affected technology is affected by a security issue. Reported affected versions include < 3.0.1.
DEVELOPING
What Happened
Evidence indicates that the affected technology is affected by a security issue. Reported affected versions include < 3.0.1.
Why This Matters
Current evidence identifies a security issue involving Critical LangChain Core, but does not yet support a more specific impact claim.
Recommended Action
Upgrade langgraph-checkpoint-sqlite to 3.0.1 or later. Identify deployments of Critical LangChain Core matching the evidenced affected versions: < 3.0.1.
Exposure
Dec 26, 2025 05:30
Mar 27, 2026 05:30
Exploitation status: UNKNOWN
Affected versions: < 3.0.1
Primary entities:
Authoritative Intelligence
Timeline
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Incident first seen
Dec 26, 2025 05:30BugSkan first recorded this incident.
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Critical LangChain Core Vulnerability Exposes Secrets via Serialization Injection - The Hacker News
Dec 26, 2025 05:30thehackernews.com ยท Vulnerability
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LangChain, LangGraph Flaws Expose Files, Secrets, Databases in Widely Used AI Frameworks - The Hacker News
Mar 27, 2026 05:30thehackernews.com ยท Vulnerability
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Latest observed development
Mar 27, 2026 05:30Most recent source or update associated with this incident.
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Material change
Aug 18, 2026 14:07recommended action updated
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Material change
Aug 18, 2026 14:07why it matters updated
Sources
thehackernews.com ยท Dec 26, 2025 05:30
A critical serialization injection vulnerability, CVE-2025-68664, has been discovered in LangChain Core, affecting its `dumps()` and `dumpd()` functions by failing to escape user-controlled dictionaries containing "lc" keys. This flaw allows attackers to instantiate arbitrary objects, potentially leading to secret extraction, prompt injection in LLM responses, and even arbitrary code execution through deserialization.
Open publisher sourcethehackernews.com ยท Mar 27, 2026 05:30
Three critical vulnerabilities (CVE-2026-34070, CVE-2025-68664, CVE-2025-67644) have been discovered in LangChain and LangGraph, widely used AI frameworks for building LLM applications. These flaws include path traversal, deserialization of untrusted data, and SQL injection, allowing attackers to access arbitrary filesystem files, leak environment secrets, and execute arbitrary SQL queries against conversation history databases.
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