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GHSA-xv6x-43gq-4hfj

PyGreSQL Might Be Vulnerable to Encoding-Based SQL Injection

Also known asCVE-2009-2940PYSEC-2009-18
Published
May 2, 2022
Updated
Jun 8, 2026
Affected
2 pkgs
Patched
1 / 2
Exploits
None indexed

EPSS Exploitation Probability

via FIRST.org ↗
2.7%probability of exploitation in next 30 days
Lower Risk84th percentile+2.12%
0.00%1.11%2.23%3.34%0.6%2.7%Dec 25Apr 26Jun 26

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

Blast Radius

2 pkgs affected
🐍pygresql🐍pygresql

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

PyGreSQL 3.8 did not use PostgreSQL’s safe string and bytea functions in its own escaping functions. As a result, applications written to use PyGreSQL’s escaping functions are vulnerable to SQL injections when processing certain multi-byte character sequences. Because the safe functions require a database connection, to maintain backwards compatibility, pg.escape_string() and pg.escape_bytea() are still available, but applications will have to be adjusted to use the new pyobj.escape_string() and pyobj.escape_bytea() functions. For example, code containing:

import pg
connection = pg.connect(...)
escaped = pg.escape_string(untrusted_input)

should be adjusted to use:

import pg
connection = pg.connect(...)
escaped = connection.escape_string(untrusted_input)

Affected Packages

2 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIpygresqlall versionsNo fix
🐍PyPIpygresql4.0&&< 4.14.1

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for pygresql. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    No patched version of pygresql has shipped for GHSA-xv6x-43gq-4hfj yet. Where your build allows, override or pin the dependency away from the vulnerable range, and apply any maintainer-recommended mitigation.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether GHSA-xv6x-43gq-4hfj is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-xv6x-43gq-4hfj. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

PyGreSQL 3.8 did not use PostgreSQL’s safe `string` and `bytea` functions in its own escaping functions. As a result, applications written to use PyGreSQL’s escaping functions are vulnerable to SQL injections when processing certain multi-byte character sequences. Because the safe functions require a database connection, to maintain backwards compatibility, `pg.escape_string()` and `pg.escape_bytea()` are still available, but applications will have to be adjusted to use the new `pyobj.escape_string()` and `pyobj.escape_bytea()` functions. For example, code containing: ```python import pg conn
O3 Security · Impact-Aware SCA

Is GHSA-xv6x-43gq-4hfj in your dependencies?

O3 detects GHSA-xv6x-43gq-4hfj across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.