CVE-2026-57204: pypdf Denial-of-Service Memory Exhaustion Vulnerability

Technical summary

CVE-2026-57204 is a resource exhaustion vulnerability in pypdf prior to version 6.13.3. The root cause is improper handling of the MAX_DECLARED_STREAM_LENGTH safeguard when a PDF content stream does not include a /Length field. Under normal circumstances, this limit prevents a single stream declaration from consuming unbounded memory during parsing. However, the implementation contains a code path that bypasses this protection when the /Length value is absent, allowing a crafted PDF to trigger memory allocation far beyond intended limits. This is classified as an Uncontrolled Resource Consumption vulnerability (CWE-400).

Business impact

For organizations and developers relying on pypdf to process user-supplied or untrusted PDFs, this vulnerability poses a service availability risk. Web applications, document processing pipelines, batch analysis tools, and any service that automatically parses PDF uploads could be forced offline or become unresponsive. The impact is heightened in multi-tenant or shared infrastructure scenarios where one malicious PDF could degrade performance for other users. While confidentiality and integrity are not at risk, availability degradation can result in lost productivity, service disruptions, and reputational damage.

Affected systems

Any deployment using pypdf versions prior to 6.13.3 is affected. This includes direct usage in Python applications, as well as downstream tools and services that bundle or depend on pypdf. Common use cases include document management systems, PDF-to-text converters, automated report generators, and integration platforms that accept user-uploaded PDFs. The vulnerability is network-accessible in scenarios where the PDF is fetched from an untrusted source or supplied by an end-user.

Exploitability

Exploitation requires user interaction—specifically, the processing of an attacker-crafted PDF by the vulnerable library. The attack vector is network-based, making it feasible for an attacker to distribute malicious PDFs via email, web forms, file-sharing services, or other channels. The low attack complexity and lack of privilege requirements lower the barrier to entry. However, the attacker cannot directly trigger parsing from a remote system; they must rely on a user or automated system to open or process the file. Once parsed, the memory exhaustion occurs deterministically, making exploitation reliable.

Remediation

Upgrade pypdf to version 6.13.3 or later, which includes a fix that properly enforces MAX_DECLARED_STREAM_LENGTH across all parsing code paths, including those handling streams without explicit /Length fields. Organizations should verify compatibility with their existing codebase and test the upgrade in a staging environment before rolling out to production. For systems where immediate patching is not feasible, consider implementing additional controls such as processing PDFs in isolated or resource-constrained containers, imposing timeout limits on parsing operations, and validating PDF integrity before processing.

Patch guidance

The fix is available in pypdf 6.13.3 and later releases. Update your Python environment using your package manager (e.g., `pip install --upgrade pypdf==6.13.3` or specify `pypdf>=6.13.3` in your requirements file). Verify the installed version with `pip show pypdf`. If you maintain downstream dependencies or applications that bundle pypdf, ensure they are updated and re-released to pull in the patched library version. Confirm the patch is applied by testing with known problematic PDF samples if available.

Detection guidance

Monitor for signs of resource exhaustion in systems that parse PDFs: watch for unexpected memory usage spikes, out-of-memory exceptions, or process crashes in pypdf-dependent services. Implement application-level logging to capture PDF parsing errors and resource warnings. At the network level, inspect inbound PDFs for suspicious characteristics (missing /Length fields combined with large declared stream sizes, unusual stream objects, etc.) if your security tools support PDF analysis. Consider implementing resource limits (memory, CPU time) at the container or process level to prevent a single malformed PDF from affecting system stability.

Why prioritize this

While the CVSS score of 6.5 (MEDIUM) reflects the requirement for user interaction and limited attack surface, the practical risk depends on your organization's exposure. Prioritize this if you: (1) process user-uploaded or externally-sourced PDFs at scale, (2) run pypdf in a shared or cloud environment where resource exhaustion affects other users, or (3) use automated or batch PDF processing without human oversight. Organizations that only process internally-generated or trusted PDFs can defer patching, but should still plan an update within your normal maintenance cycle.

Risk score, explained

The CVSS 3.1 score of 6.5 (MEDIUM) reflects a network-accessible, low-complexity attack with no privilege requirements (AV:N/AC:L/PR:N) but mandatory user interaction (UI:R). Impact is limited to availability (A:H), with no effect on confidentiality or integrity (C:N/I:N). The score appropriately balances the ease of crafting a malicious PDF against the need for human or automated action to parse it, and against the high likelihood of causing a denial of service once triggered.

Frequently asked questions