BlackTreeIndependent security intelligence
← Back to the CVE catalogue
Full vulnerability report · 2023
CVE-2022-45786High confidence

Apache AGE: Python and Golang drivers allow data manipulation and exposure due to SQL injection

Apache Software Foundation · Apache AGE

8.1HighCVSS 3.1
Recommended action
Within 7 days

High technical severity; prioritise exposed affected systems while verifying vendor guidance.

Fix not verified
Optional official sources

National CERT insights
?CERT means Computer Emergency Response Team; CSIRT is the closely related term Computer Security Incident Response Team.

Select the national-authority views to include. The exact source language is shown on each matched advisory. Your choice is remembered on this device and encoded in the shareable URL.

Official European source

ENISA European Vulnerability Database

Official EUVD identifiers, advisory evidence and known-exploited context. Missing fields are not treated as evidence of low risk.

1 current
ENISA EUVD identifier

EUVD-2023-0642

No EUVD known-exploited evidence

ENISA has published the identifier mapping but no EUVD description has been stored yet.

EUVD state
Present in the current official mapping
Known exploitation
Not present in the current ENISA EUVD known-exploited dataset. This is not proof of no exploitation.
ENISA score
Not supplied in the stored EUVD record
Advisory evidence
No linked advisory details stored yet
Recommended actionWithin 7 days

High technical severity; prioritise exposed affected systems while verifying vendor guidance.

Fix not verified
01

What, why and how

There are issues with the AGE drivers for Golang and Python that enable SQL injections to occur. This impacts AGE for PostgreSQL 11 & AGE for PostgreSQL 12, all versions up-to-and-including 1.1.0, when using those drivers. The fix is to update to the latest Golang and Python drivers in addition to the latest version of AGE that is used for PostgreSQL 11 or  PostgreSQL 12. The update of AGE will add a new function to enable parameterization of the cypher() function, which, in conjunction with the driver updates, will resolve this issue. Background (for those who want more information): After thoroughly researching this issue, we found that due to the nature of the cypher() function, it was not easy to parameterize the values passed into it. This enabled SQL injections, if the developer of the driver wasn't careful. The developer of the Golang and Pyton drivers didn't fully utilize parameterization, likely because of this, thus enabling SQL injections. The obvious fix to this issue is to use parameterization in the drivers for all PG SQL queries. However, parameterizing all PG queries is complicated by the fact that the cypher() function call itself cannot be parameterized directly, as it isn't a real function. At least, not the parameters that would take the graph name and cypher query. The reason the cypher() function cannot have those values parameterized is because the function is a placeholder and never actually runs. The cypher() function node, created by PG in the query tree, is transformed and replaced with a query tree for the actual cypher query during the analyze phase. The problem is that parameters - that would be passed in and that the cypher() function transform needs to be resolved - are only resolved in the execution phase, which is much later. Since the transform of the cypher() function needs to know the graph name and cypher query prior to execution, they can't be passed as parameters. The fix that we are testing right now, and are proposing to use, is to create a function that will be called prior to the execution of the cypher() function transform. This new function will allow values to be passed as parameters for the graph name and cypher query. As this command will be executed prior to the cypher() function transform, its values will be resolved. These values can then be cached for the immediately following cypher() function transform to use. As added features, the cached values will store the calling session's pid, for validation. And, the cypher() function transform will clear this cached information after function invocation, regardless of whether it was used. This method will allow the parameterizing of the cypher() function indirectly and provide a way to lock out SQL injection attacks.

What

There are issues with the AGE drivers for Golang and Python that enable SQL injections to occur. This impacts AGE for PostgreSQL 11 & AGE for PostgreSQL 12, all versions up-to-and-including 1.1.0, when using those drivers. The fix is to update to the latest Golang and Python drivers in addition to the latest version of AGE that is used for PostgreSQL 11 or  PostgreSQL 12. The update of AGE will add a new function to enable parameterization of the cypher() function, which, in conjunction with the driver updates, will resolve this issue. Background (for those who want more information): After thoroughly researching this issue, we found that due to the nature of the cypher() function, it was not easy to parameterize the values passed into it. This enabled SQL injections, if the developer of the driver wasn't careful. The developer of the Golang and Pyton drivers didn't fully utilize parameterization, likely because of this, thus enabling SQL injections. The obvious fix to this issue is to use parameterization in the drivers for all PG SQL queries. However, parameterizing all PG queries is complicated by the fact that the cypher() function call itself cannot be parameterized directly, as it isn't a real function. At least, not the parameters that would take the graph name and cypher query. The reason the cypher() function cannot have those values parameterized is because the function is a placeholder and never actually runs. The cypher() function node, created by PG in the query tree, is transformed and replaced with a query tree for the actual cypher query during the analyze phase. The problem is that parameters - that would be passed in and that the cypher() function transform needs to be resolved - are only resolved in the execution phase, which is much later. Since the transform of the cypher() function needs to know the graph name and cypher query prior to execution, they can't be passed as parameters. The fix that we are testing right now, and are proposing to use, is to create a function that will be called prior to the execution of the cypher() function transform. This new function will allow values to be passed as parameters for the graph name and cypher query. As this command will be executed prior to the cypher() function transform, its values will be resolved. These values can then be cached for the immediately following cypher() function transform to use. As added features, the cached values will store the calling session's pid, for validation. And, the cypher() function transform will clear this cached information after function invocation, regardless of whether it was used. This method will allow the parameterizing of the cypher() function indirectly and provide a way to lock out SQL injection attacks.

Why

Attacker-controlled data is not kept separate from SQL query syntax, allowing the intended database operation to be changed.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

What

There are issues with the AGE drivers for Golang and Python that enable SQL injections to occur. This impacts AGE for PostgreSQL 11 & AGE for PostgreSQL 12, all versions up-to-and-including 1.1.0, when using those drivers. The fix is to update to the latest Golang and Python drivers in addition to the latest version of AGE that is used for PostgreSQL 11 or  PostgreSQL 12. The update of AGE will add a new function to enable parameterization of the cypher() function, which, in conjunction with the driver updates, will resolve this issue. Background (for those who want more information): After thoroughly researching this issue, we found that due to the nature of the cypher() function, it was not easy to parameterize the values passed into it. This enabled SQL injections, if the developer of the driver wasn't careful. The developer of the Golang and Pyton drivers didn't fully utilize parameterization, likely because of this, thus enabling SQL injections. The obvious fix to this issue is to use parameterization in the drivers for all PG SQL queries. However, parameterizing all PG queries is complicated by the fact that the cypher() function call itself cannot be parameterized directly, as it isn't a real function. At least, not the parameters that would take the graph name and cypher query. The reason the cypher() function cannot have those values parameterized is because the function is a placeholder and never actually runs. The cypher() function node, created by PG in the query tree, is transformed and replaced with a query tree for the actual cypher query during the analyze phase. The problem is that parameters - that would be passed in and that the cypher() function transform needs to be resolved - are only resolved in the execution phase, which is much later. Since the transform of the cypher() function needs to know the graph name and cypher query prior to execution, they can't be passed as parameters. The fix that we are testing right now, and are proposing to use, is to create a function that will be called prior to the execution of the cypher() function transform. This new function will allow values to be passed as parameters for the graph name and cypher query. As this command will be executed prior to the cypher() function transform, its values will be resolved. These values can then be cached for the immediately following cypher() function transform to use. As added features, the cached values will store the calling session's pid, for validation. And, the cypher() function transform will clear this cached information after function invocation, regardless of whether it was used. This method will allow the parameterizing of the cypher() function indirectly and provide a way to lock out SQL injection attacks.

Why

Attacker-controlled data is not kept separate from SQL query syntax, allowing the intended database operation to be changed.

How

An attacker operating through a network path may attempt exploitation without authentication or user interaction. If successful, the issue may cause the confidentiality, integrity or availability impact described by the vendor.

02

Exploit reality and attack path

CVSS severity, EPSS forecast probability, public exploit material and CISA-confirmed exploitation are separate signals.

Observed exploitation
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
No confirmed evidence

No CISA KEV match was present at the last successful refresh. This means no confirmation from that source, not proof of no exploitation.

Public PoC / exploit material
?Confirmed exploitation and public exploit material are separate signals. Attacks can occur without public proof-of-concept or exploit code.
None recorded

No exploit-tagged reference or CISA SSVC proof-of-concept state is currently recorded. Research may still exist outside the structured feeds.

Likely attack path
a network path → Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection') → cause the confidentiality, integrity or availability impact described by the vendor
Attack surface
Network
Privileges required
None: unauthenticated exploitation is possible
User interaction
None
Attack complexity
High: exploitation depends on specific conditions
Security boundary
Unchanged: impact remains within the vulnerable component's security authority
Weakness
?CWE means Common Weakness Enumeration: a standard category for the underlying weakness.
CWE-89

CWE-89: Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection'). 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.

CVSS vector
?CVSS means Common Vulnerability Scoring System. The vector records the metric values used to calculate technical severity.
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:H/I:H/A:H

Common Vulnerability Scoring System 3.1: the compact vector below is decoded into plain language.

AVNetworkAttack vector: The vulnerable component can be reached over a network.ACHighAttack complexity: Successful exploitation depends on specific conditions outside the attacker's direct control.PRNonePrivileges required: The attacker does not need an account or existing privileges.UINoneUser interaction: No action by another user is required.SUnchangedScope: The security impact remains within the vulnerable component's authority.CHighConfidentiality impact: A successful attack can cause a major loss.IHighIntegrity impact: A successful attack can cause a major loss.AHighAvailability impact: A successful attack can cause a major loss.
Post-exploitation / living off the land
No specific living-off-the-land technique is confirmed in the structured sources. Monitor normal administration tools for activity inconsistent with the affected service's baseline.
NetworkUnauthenticatedCWE-89
A

Official authority intelligence

Only matched European and national findings are included. Language selectors and unavailable sources are omitted.

03

Patch and workaround

Operational remediation based on structured source evidence.

Status
?Patch availability is based on structured fixed-version fields and authoritative update references. If no fix is verified, check the vendor advisory before making a change.
Fix not verified
Affected
Apache AGE for PostgreSQL 12 ≤ 1.1.0; Apache AGE for PostgreSQL 11 ≤ 1.1.0
Fixed
No fixed version is explicitly recorded in the structured CVE data.
Action
No verified patch reference is present in the current structured sources. Check the vendor advisory before making a change.
Workaround
No verified workaround is recorded. If business-safe, reduce exposure to the affected interface and allow only trusted sources until authoritative guidance is available.
04

Evidence and provenance

Published 4 Feb 2023 · Last source change 26 Mar 2025, 13:58 UTC · CWE-89 · Improper Neutralization of Special Elements used in an SQL Command ('SQL Injection')

CVE recordCVE.org · 5.1
CVSS sourceNIST NVD
EPSS source
?The date BlackTree first stored a score for this CVE from the daily FIRST EPSS feed.
FIRST · tracked since 2026-08-14
European sourceENISA EUVD · EUVD-2023-0642
Product sourceCNA
Remediation sourceCVE/CNA references
CWE sourceCNA
NVD statusNVD modified after enrichment

Core structured fields are present and their contributing authorities are shown above.

Material change intelligence

What changed after publication

View recent updates →

No material field changes have been recorded since change tracking began. Routine source refreshes and cosmetic edits are intentionally excluded.

Material fields only · duplicate refreshes suppressed · history retained for the configured operational retention period
Technical terms and abbreviations used in this report
CVE
Common Vulnerabilities and Exposures: the public identifier for one disclosed vulnerability.
CVSS
Common Vulnerability Scoring System: a technical severity framework; it is not patching priority by itself.
EPSS
Exploit Prediction Scoring System: FIRST's estimate of the probability that exploitation activity will be observed in the next 30 days; it is a forecast, not confirmation.
CWE
Common Weakness Enumeration: the standard category describing the underlying software or hardware weakness.
CNA
CVE Numbering Authority: an organisation authorised to assign and publish CVE records.
CISA ADP
Cybersecurity and Infrastructure Security Agency Authorized Data Publisher: structured enrichment added to a CVE record.
NVD
National Vulnerability Database: NIST's enrichment service for CVE records.
CERT / CSIRT
A computer security incident response team that publishes warnings or coordinates incident response.
PoC
Proof of concept: public material that demonstrates or helps reproduce exploitation.
CSAF
Common Security Advisory Framework: a machine-readable format for security advisories.
LoTL
Living off the land: abuse of legitimate tools or system functions during an attack.
Free version - for non-commercial use only.CVE-2022-45786 · cve.blacktree.nl