CVE-2025-67644VulnerabilityPublished 10 Dec 2025

CVE-2025-67644: langchain-ai langgraph · SQL Injection

Affects langchain-ai langgraphSource CVE Database V5

Not known to be exploited · CVSS 7.3 High : upgrade to 3.0.1 soon.

Data as of 26 Oct 2026, 08:11 UTC

CVSS 3.1 base score

7.3High

How severe the flaw is on the 0–10 CVSS scale.

EPSS: 2.3% chance of exploitation in 30 days – higher than 83% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
Patch: Available – fixed in 3.0.1

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:C/C:H/I:L/A:N

Attack Vector: Local
Attack Complexity: Low
Privileges Required: Low
User Interaction: None
Scope: Changed
Confidentiality: High
Integrity: Low
Availability: None

Bold values are the worst case: easiest to exploit or largest impact.

Attack Vector: Local: The vulnerable component is not bound to the network stack and the attacker’s path is via read/write/execute capabilities. Either: the attacker exploits the vulnerability by accessing the target system locally (e.g., keyboard, console), or remotely (e.g., SSH); or the attacker relies on User Interaction by another person to perform actions required to exploit the vulnerability (e.g., tricking a legitimate user into opening a malicious document).
Attack Complexity: Low: Specialized access conditions or extenuating circumstances do not exist. An attacker can expect repeatable success against the vulnerable component.
Privileges Required: Low: The attacker is authorized with (i.e., requires) privileges that provide basic user capabilities that could normally affect only settings and files owned by a user. Alternatively, an attacker with Low privileges may have the ability to cause an impact only to non-sensitive resources.
User Interaction: None: The vulnerable system can be exploited without any interaction from any user.
Scope: Changed: An exploited vulnerability can affect resources beyond the security scope managed by the security authority of the vulnerable component. In this case, the vulnerable component and the impacted component are different and managed by different security authorities.
Confidentiality: High: There is total loss of confidentiality, resulting in all resources within the impacted component being divulged to the attacker. Alternatively, access to only some restricted information is obtained, but the disclosed information presents a direct, serious impact.
Integrity: Low: Modification of data is possible, but the attacker does not have control over the consequence of a modification, or the amount of modification is limited. The data modification does not have a direct, serious impact on the impacted component.
Availability: None: There is no impact to availability within the impacted component.

Definitions: FIRST CVSS v3.1 specification.

Exploitation evidence

Disclosed: evidence found.
CVE published 10 Dec 2025
Detectable: no evidence on record.
No public nuclei template indexed
Weaponised: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors

A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 2026-10-26.

Disclosed: The CVE record is public on cve.org. Its publication is t = 0.
Detectable: A public nuclei template can find exposed instances, for defenders and attackers alike.
Weaponised: Public exploit code exists in Metasploit or Exploit-DB, or CISA SSVC reports a public proof of concept.
Exploited in the wild: CISA KEV lists it, CISA SSVC rates exploitation active, or a source reports attacks.
Observed by OffSeq Mirage: OffSeq Mirage honeypot sensors recorded attack traffic for this CVE, or found exposed hosts without attack traffic.

Moments are spaced evenly, not to scale; a dashed line marks a gap of six months or more. Deltas count from t = 0. Sources that give only a date (CISA KEV, Exploit-DB, or a time of exactly 00:00Z) read “same day” rather than hours. Metasploit modules carry the flaw’s disclosure date, not their release date, and nuclei templates carry no date, so both appear above but not on the timeline.

What to do

Upgrade langchain-ai/langgraph to 3.0.1.

Affected software

Product	Affected	Fixed in
GitHublangchain-ai/langgraph`pkg:github/langchain-ai/langgraph`Other threats	Affected <3.0.1	Fixed in 3.0.1

Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.

AI-suggested

1. Immediate upgrade to langgraph version 3.0.1 or later, where the vulnerability is fixed. 2. Implement strict input validation and sanitization on all metadata filter keys before they are processed by the checkpoint system, ensuring that only expected keys with safe characters are accepted. 3. Restrict access to the checkpointing functionality and metadata inputs to trusted users and systems only, minimizing the risk of local exploitation. 4. Employ application-layer firewalls or runtime application self-protection (RASP) tools that can detect and block suspicious SQL query patterns indicative of injection attempts. 5. Conduct code reviews and penetration testing focused on metadata handling and checkpoint operations to identify any residual injection vectors. 6. Monitor logs for unusual query patterns or errors related to checkpoint searches that could indicate attempted exploitation. 7. Educate developers and security teams about the risks of interpolating untrusted input directly into SQL queries and promote the use of parameterized queries or ORM frameworks that inherently prevent injection. 8. For organizations unable to upgrade immediately, implement compensating controls such as input filtering proxies or sandboxing of the checkpointing process to limit potential damage.

Description

LangGraph SQLite Checkpoint is an implementation of LangGraph CheckpointSaver that uses SQLite DB (both sync and async, via aiosqlite). Versions 3.0.0 and below are vulnerable to SQL injection through the checkpoint implementation. Checkpoint allows attackers to manipulate SQL queries through metadata filter keys, affecting applications that accept untrusted metadata filter keys (not just filter values) in checkpoint search operations. The _metadata_predicate() function constructs SQL queries by interpolating filter keys directly into f-strings without validation. This issue is fixed in version 3.0.1.

Impact

For European organizations, this vulnerability can lead to unauthorized disclosure of sensitive data stored within langgraph's SQLite databases, potentially exposing intellectual property, user data, or operational metadata. The ability to manipulate SQL queries through untrusted metadata filter keys could allow attackers to extract confidential information or subtly alter data integrity, undermining trust in AI-driven applications that rely on langgraph for state persistence. Given the increasing adoption of AI and machine learning frameworks in sectors such as finance, healthcare, and critical infrastructure across Europe, exploitation could have regulatory and reputational consequences, including violations of GDPR due to data breaches. The local attack vector implies that attackers may need some level of access, such as compromised internal accounts or insider threats, which are realistic in complex enterprise environments. The lack of known exploits suggests the window for proactive mitigation is still open, but the high CVSS score and scope change indicate that the vulnerability should be treated as a priority. Failure to address this could lead to lateral movement within networks, data exfiltration, or manipulation of AI model states, impacting decision-making processes and operational continuity.

CWE-89Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') (opens in a new tab)
Base weaknessLikelihood of exploit: HighCWE Top 25 (2025): #2OWASP Top 10 A05:2025: Injection (opens in a new tab)
The product constructs all or part of an SQL command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended SQL command when it is sent to a downstream component. Without sufficient removal or quoting of SQL syntax in user-controllable inputs, the generated SQL query can cause those inputs to be interpreted as SQL instead of ordinary user data.
Architecture and Design · Libraries or Frameworks
Use a vetted library or framework that does not allow this weakness to occur or provides constructs that make this weakness easier to avoid.
Architecture and Design · Parameterization
If available, use structured mechanisms that automatically enforce the separation between data and code. These mechanisms may be able to provide the relevant quoting, encoding, and validation automatically, instead of relying on the developer to provide this capability at every point where output is generated.
Architecture and Design · Operation · Environment Hardening
Run your code using the lowest privileges that are required to accomplish the necessary tasks. If possible, create isolated accounts with limited privileges that are only used for a single task. That way, a successful attack will not immediately give the attacker access to the rest of the software or its environment.
OWASP Cheat Sheets
Query Parameterization (opens in a new tab)
Unvalidated Redirects and Forwards (opens in a new tab)
XML Security (opens in a new tab)
XML External Entity Prevention (opens in a new tab)
File Upload (opens in a new tab)
OWASP ASVS 4.0.3
V5.3.4 (opens in a new tab)
V5.3.5 (opens in a new tab)
V1.5.1 (opens in a new tab)
Attack patterns
Command Line Execution through SQL Injection (opens in a new tab)
Object Relational Mapping Injection (opens in a new tab)
SQL Injection through SOAP Parameter Tampering (opens in a new tab)
Expanding Control over the Operating System from the Database (opens in a new tab)
SQL Injection (opens in a new tab)
From MITRE CWE, MITRE CAPEC and OWASP (Top 10, OpenCRE).

References

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Exploitation evidence

What to do

Affected software

Description

AI analysisMachine-generated, updated 18 Dec 2025, 00:52 UTC

WeaknessesCWE-89

Technical details

References

Community reviews

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