CVE-2025-6985 — XXE Vulnerability in langchain-ai/langchain
The HTMLSectionSplitter class in langchain-text-splitters version 0.3.8 is vulnerable to XML External Entity (XXE) attacks due to unsafe XSLT parsing. This vulnerability arises because the class allows the use of arbitrary XSLT stylesheets, which are parsed using lxml.etree.parse() and lxml.etree.XSLT() without any hardening measures. In lxml versions up to 4.9.x, external entities are resolved by default, allowing attackers to read arbitrary local files or perform outbound HTTP(S) fetches. In lxml versions 5.0 and above, while entity expansion is disabled, the XSLT document() function can still read any URI unless XSLTAccessControl is applied. This vulnerability allows remote attackers to gain read-only access to any file the LangChain process can reach, including sensitive files such as SSH keys, environment files, source code, or cloud metadata. No authentication, special privileges, or user interaction are required, and the issue is exploitable in default deployments that enable custom XSLT.
Who exploits it and how urgent it is
A 0–100 score combining confirmed exploitation, ransomware and APT use, public exploits, EPSS and severity.
How the score was calculated
- EPSS 0.5% (30-day exploitation probability)+6
- Technical severity (high)+6
- CISA SSVC: exploitation "poc"+5
- Automatable exploitation (SSVC)+3
The score orders the patch queue; it does not replace your asset context (internet exposure, criticality, compensating controls).
Triage
Is it exploited, how likely is exploitation, what does it touch, and how severe do the sources call it.
CISA SSVC assessment CISA
Three decision points CISA publishes for the CVEs it assesses (SSVC 2.0.3). A stakeholder decision, not a severity score.
Remediation
Fixes and mitigations documented by the sources — linked to the original advisory.
- Pip Langchain-text-splitters: fixed in version 0.3.9 — github.com (GitHub Security Advisories)
First 24 hours
Ordered from the record’s own fields — exposure first, because you cannot patch what you have not found. A rule-generated starting point.
- Identify exposed assets running the affected vendor/product/version combinations (Langchain-ai Langchain-ai/langchain, Pip Langchain-text-splitters).
- The attack is network-based and needs no privileges: restrict exposure (ACLs, VPN, WAF) until patched.
- Apply the fixed version or the patch documented under Remediation.
- Search available logs for exploit probes matching the vulnerability class (injection), errors and authentication anomalies.
Affected scope
Vendor, product and versions as the sources word them.
| Vendor | Product | Versions | Status | Source |
|---|---|---|---|---|
| Langchain-ai | Langchain-ai/langchain | ≤ latest | Vulnerable | CVE Program (cve.org) e CISA ADP |
| Pip | Langchain-text-splitters | < 0.3.9 | Vulnerable | GitHub Security Advisories |
Attack characteristics
The CVSS vector, decoded. It describes the attack, not your exposure to it.
Every base score collected
Sources score independently and may disagree; each row says who scored it and under which version.
| Score | Version | Severity | Expl. | Impact | Scored by |
|---|---|---|---|---|---|
| 7.5 | CVSS 3.0 | High | 3.9 | 3.6 | security@huntr.dev via NIST National Vulnerability Database |
| 7.5 | CVSS 3.0 | High | — | — | GitHub, Inc. via GitHub Security Advisories |
| 7.5 | CVSS 3.0 | High | — | — | @huntr_ai via CVE Program (cve.org) e CISA ADP |
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:N/A:N (score shown at the top: security@huntr.dev) Weakness MITRE
Weakness class according to MITRE’s CWE catalog.
Detection
Read off the CVSS vector and the weakness class. Starting points, not tested rules.
- Prioritize edge telemetry for the network-reachable component (proxy, WAF, IDS/IPS).
- Look for parameters with command/query metacharacters and unexpected child processes of the service.
Timeline
What happened to this CVE, newest first.
- 2026
- Fix documented
- Affected products added · pip/langchain-text-splitters
- Affected products added · langchain-ai/langchain-ai/langchain
- SSVC assessment updated
- Record published
- CVSS changed · 7.5
- Source status changed · → Deferred
- Record created in this database
- 2025
- CVE published
Source activity
Repeated readings are counted rather than listed.
- 1× References added · Oct 19, 2026 – Oct 19, 2026
- 1× Official description updated · Oct 19, 2026 – Oct 19, 2026
References
5 on the record
Elsewhere on this site
Related CVEs (same products)
- Medium CVE-2026-55443 LangChain: Path traversal and sandbox escape in LangChain file-search middleware and loaders Jun 22, 2026
- High CVE-2026-44843 LangChain: Unsafe deserialization of attacker-controlled LangChain objects through overly broad `load()` allowlists May 26, 2026
- Medium CVE-2026-40087 LangChain has incomplete f-string validation in prompt templates Apr 9, 2026
- High CVE-2026-34070 LangChain Core has Path Traversal vulnerabilites in legacy `load_prompt` functions Mar 31, 2026
- Low CVE-2026-26013 LangChain affected by SSRF via image_url token counting in ChatOpenAI.get_num_tokens_from_messages Feb 10, 2026
- High CVE-2024-58340 LangChain <= 0.3.1 MRKLOutputParser ReDoS Jan 12, 2026
Not in any source we poll
Listed rather than left blank: an empty field and an unmeasured one look identical on screen, and only one is a reason to look elsewhere.
- No confirmed IOCs, IP addresses, domains, file hashes, or malware artifacts supplied.
- No organization-specific asset inventory, compensating-control status, or patch deployment evidence supplied.
- No exploit packet captures, log samples, or incident case IDs supplied.
Answered from this record
Text assembled only from the fields above — no additional claims.
What should defenders know first?
CVE-2025-6985 is "XXE Vulnerability in langchain-ai/langchain", rated High. It affects Langchain-ai/langchain (Langchain-ai); versions are in the scope table. It is not in CISA KEV, which does not rule out exploitation. CVSS 7.5 describes technical severity. EPSS 0.51% estimates the probability of exploitation in 30 days; neither replaces your asset context. First verify whether exposed or business-critical assets run the affected versions, apply vendor fixes or mitigations, and preserve logs for review.
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