Attack ChainAIDerived
Hypothetical attack flow derived from CVE metadata – not a confirmed exploit chain
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AccessAuthenticate as low-privileged DB user
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ExploitQuery pg_stats before ANALYZE refresh
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ImpactRecover statistics describing original unmasked data
Vulnerability Assessment
| Weakness |
CWE
ASVS 5.0
V14 - Data Protection Sensitive data in outbound message
|
| Exploitation Conditions | Exploitation requires that an administrator has applied PostgreSQL Anonymizer static masking to a table AND that no ANALYZE has yet run on that table (manually or via autovacuum) to overwrite the cached statistics - this is the explicit trigger window stated in the description. The attacker must be an authenticated PostgreSQL user (PR:L) with privileges to read the pg_stats view for the affected relation. What LIMITS exploitation: the exposure is time-bounded and self-healing (any ANALYZE or routine autovacuum eliminates it), the attacker needs valid database credentials, and only statistical metadata (common values, histograms, min/max bounds) about the original data is exposed - not full row contents. The impact is confined to deployments that rely on static masking and assume it immediately purges all traces of original data. |
| Impact | This is a genuine but low-urgency information-disclosure issue, not a high-severity emergency. The CVSS 3.1 base score is 4.3 (Medium) with vector AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N - meaning low-privileged but authenticated access, no user interaction, and only a limited confidentiality impact (no integrity or availability impact). No EPSS score was supplied, the CVE is not listed in CISA KEV, and no exploit code or working PoC reference was provided (the single reference is a Dalibo GitLab issue-tracker entry, not an exploit). The vuln.today decision label is 'this_month', consistent with a real-but-not-critical finding to be remediated on a normal patch cadence rather than as an emergency. The signals are internally consistent: Medium CVSS, no evidence of exploitation, limited impact scoped to statistical metadata rather than full record contents. The practical risk is that 'anonymized' data is not as protected as an operator assumes, because pre-masking statistics linger in pg_stats; this is an assurance/compliance gap more than a direct breach vector. No key signals are in open conflict, though EPSS is simply absent rather than low. |
| Exploit ScenarioDerived | After an operator runs static masking on a table expecting the original values to be gone, a low-privileged authenticated database user queries the pg_stats view before any ANALYZE (manual or autovacuum) refreshes the statistics, and reads cached statistics - such as most-common-values, histogram bounds, and min/max - that describe the original, unmasked data. No public exploit or PoC code is identified at time of analysis; the only reference is a vendor issue-tracker entry. Exploitation is a straightforward SQL read requiring no special tooling. |
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Alert meAnalysisAIv1 – Oct 28, 2026
PostgreSQL Anonymizer before 3.3.0 can leave statistics derived from original, pre-masking data visible in pg_stats after static masking has been applied, until an ANALYZE operation or autovacuum refreshes the table statistics. An authenticated PostgreSQL user with access to pg_stats for the affected relation could read common values, histograms, or range bounds that reveal information about the original data; the exposure is limited to metadata rather than row contents and is time-bounded because routine statistics maintenance clears it. No public exploit identified at time of analysis, and the issue is rated CVSS 4.3 with a fix in 3.3.0.
RemediationAI
Upgrade PostgreSQL Anonymizer to 3.3.0 or later, per the vendor reference at https://gitlab.com/dalibo/postgresql_anonymizer/-/issues/722. The described behavior indicates that running ANALYZE on a table after static masking, or allowing autovacuum to do so, refreshes the statistics and removes the stale pg_stats exposure; as an interim measure, administrators who cannot upgrade immediately should run ANALYZE on masked tables promptly. Because exploitation requires an authenticated PostgreSQL user with privileges to read pg_stats for the affected relation, access to pg_stats on masked tables should be limited to users who require it.
Affected VersionsENISA
Affected Packages
Source: OSV (Open Source Vulnerabilities)
Affects your stack
Affects 1 package in euvd
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Technical ContextAI · show details
PostgreSQL Anonymizer is a PostgreSQL extension that provides masking capabilities, including static masking that rewrites table data. PostgreSQL maintains table statistics in pg_statistic, exposed through the pg_stats view, containing metadata such as most common values, histograms, and min/max bounds. CWE-202 describes exposure of sensitive information through data queries. In this case, when static masking changes table contents but the statistics cache still reflects the pre-masking data, pg_stats can reveal statistical information about the original values until an ANALYZE operation or autovacuum refreshes the table statistics. The trigger window is explicit: static masking has been applied and no ANALYZE has yet run on that table. The exposure is limited to statistical metadata, not full row contents.
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Severity by source
AV:N/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N
Authenticated DB user needed to read pg_stats so PR:L; reachable over normal database connection (AV:N/AC:L); only statistical metadata leaks, giving C:L with no integrity or availability impact.
Primary rating from Vendor (PostgreSQL).
CVSS VectorVendor: PostgreSQL
Lifecycle Timeline
1DescriptionCVE.org
PostgreSQL Anonymizer contains a vulnerability related to static masking and statistics persistence. Statistics pertaining to the original data remain visible in pg_stats until an ANALYZE operation is performed on the table, either manually or by autovacuum. This issue is fixed in PostgreSQL Anonymizer 3.3.0 and later versions.
Threat Intelligence Overview
How this decision was reached
The engine reads each signal below and applies a fixed list of rules from top to bottom. The first rule that matches sets the recommended action – like a statement, every line is shown.
What every action level means
SSVC AssessmentENISA
Priority Score
Attack Technique
Information disclosure occurs when an application unintentionally exposes sensitive data that aids attackers in reconnaissance or directly compromises security.
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