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pgjdbc: Unbounded PBKDF2 iterations in SCRAM authentication allows CPU exhaustion DoS

High severity GitHub Reviewed Published Apr 28, 2026 in pgjdbc/pgjdbc

Package

maven org.postgresql:postgresql (Maven)

Affected versions

>= 42.2.0, < 42.7.11

Patched versions

42.7.11

Description

Summary

pgjdbc is vulnerable to a client-side denial of service during SCRAM-SHA-256 authentication.

Impact

A malicious server can instruct the driver to perform SCRAM authentication with a very large iteration count.
With a large enough value, the client spends an unbounded amount of CPU time inside PBKDF2 before authentication can fail.
A single attempt ties up a CPU core. Repeated or concurrent attempts exhaust client CPU and can wedge connection pools.

In affected versions, loginTimeout did not fully mitigate this problem. When loginTimeout expired, the caller could stop waiting, but the worker thread performing the connection attempt could continue running and burning CPU inside the SCRAM PBKDF2 computation.

This issue affects availability. It does not provide authentication bypass, privilege escalation, or direct password disclosure.

A user is vulnerable when all of the following are true:

  1. The connection uses SCRAM-SHA-256 authentication.
  2. The client reaches a malicious, compromised, or attacker-controlled PostgreSQL endpoint.
  3. That endpoint sends a very large SCRAM PBKDF2 iteration count in the server-first-message.

In practice, that can happen in these situations:

  • the application lets end users or tenants supply their own database connection details (as in many BI, reporting, analytics, ETL, and low-code platforms), so a user can point the shared client host at a server they control
  • the application accepts connection strings, hostnames, or JDBC URLs from user input, configuration uploaded by users, or other untrusted sources
  • the application is configured to connect to a PostgreSQL server that is itself malicious or later becomes compromised
  • the application connects through an untrusted proxy, relay, tunnel, bastion, or connection-pooling service that can act as the PostgreSQL server
  • an attacker can redirect the client to a fake PostgreSQL endpoint by manipulating DNS, service discovery, Kubernetes service resolution, /etc/hosts, environment variables, or similar indirection
  • an active network attacker on the path can impersonate the server because the connection does not strongly verify server identity (for example, sslmode lower than verify-full, or trusting a CA that signs hosts outside the operator's control)

The issue is more damaging when the application uses connection retries, many parallel connection attempts, or loginTimeout and assumes the timeout fully stops the work.

Patches

The patch introduces a new connection property, scramMaxIterations, with a default of 100K. The client now rejects SCRAM server messages that advertise more PBKDF2 iterations than the configured cap before starting the PBKDF2 computation begins.

Workarounds

Until a patched version of pgjdbc is deployed, the following measures reduce exposure:

  1. Only connect to trusted PostgreSQL servers whose identity is verified.
    Connect only to trusted PostgreSQL servers, and verify server identity with TLS using sslmode=verify-full and a trusted CA.
    TLS without certificate and hostname verification is not sufficient as an active network attacker can still impersonate the server.

  2. Do not rely on loginTimeout as a complete mitigation on unpatched versions.
    On affected versions, loginTimeout can stop the waiting caller while the worker thread continues spending CPU.

  3. Avoid SCRAM on untrusted or interceptable connection paths.
    For those paths, use an authentication method that does not let the server choose a SCRAM PBKDF2 iteration count.

  4. Reduce blast radius operationally.
    Limit parallel connection attempts, add retry backoff, isolate connection establishment in a separate worker or process when possible, and apply CPU or container limits where appropriate.

  5. On trusted servers you control, keep SCRAM iteration counts at ordinary values.
    This does not defend against an attacker-controlled server, but it avoids unnecessary client cost when talking to legitimate servers.

References

@sehrope sehrope published to pgjdbc/pgjdbc Apr 28, 2026
Published by the National Vulnerability Database Apr 29, 2026
Published to the GitHub Advisory Database May 5, 2026
Reviewed May 5, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(9th percentile)

Weaknesses

Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated. Learn more on MITRE.

CVE ID

CVE-2026-42198

GHSA ID

GHSA-98qh-xjc8-98pq

Source code

Credits

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