CVE-2025-66199
Issue summary: A TLS 1.3 connection using certificate compression can be forced to allocate a large buffer before decompression without checking against the configured certificate size limit.
Impact summary: An attacker can cause per-connection memory allocations of up to approximately 22 MiB and extra CPU work, potentially leading to service degradation or resource exhaustion (Denial of Service).
In affected configurations, the peer-supplied uncompressed certificate length from a CompressedCertificate message is used to grow a heap buffer prior to decompression. This length is not bounded by the max_cert_list setting, which otherwise constrains certificate message sizes. An attacker can exploit this to cause large per-connection allocations followed by handshake failure. No memory corruption or information disclosure occurs.
This issue only affects builds where TLS 1.3 certificate compression is compiled in (i.e., not OPENSSL_NO_COMP_ALG) and at least one compression algorithm (brotli, zlib, or zstd) is available, and where the compression extension is negotiated. Both clients receiving a server CompressedCertificate and servers in mutual TLS scenarios receiving a client CompressedCertificate are affected. Servers that do not request client certificates are not vulnerable to client-initiated attacks.
Users can mitigate this issue by setting SSL_OP_NO_RX_CERTIFICATE_COMPRESSION to disable receiving compressed certificates.
The FIPS modules in 3.6, 3.5, 3.4 and 3.3 are not affected by this issue, as the TLS implementation is outside the OpenSSL FIPS module boundary.
OpenSSL 3.6, 3.5, 3.4 and 3.3 are vulnerable to this issue.
OpenSSL 3.0, 1.1.1 and 1.0.2 are not affected by this issue.
| Software | From | Fixed in |
|---|---|---|
| openssl / openssl | 3.3.0 | 3.3.6 |
| openssl / openssl | 3.4.0 | 3.4.4 |
| openssl / openssl | 3.5.0 | 3.5.5 |
| openssl / openssl | 3.6.0 | 3.6.1 |
- https://github.com/openssl/openssl/commit/3ed1f75249932b155eef993a8e66a99cb98bfef4
- https://github.com/openssl/openssl/commit/6184a4fb08ee6d7bca570d931a4e8bef40b64451
- https://github.com/openssl/openssl/commit/895150b5e021d16b52fb32b97e1dd12f20448be5
- https://github.com/openssl/openssl/commit/966a2478046c311ed7dae50c457d0db4cafbf7e4
- https://openssl-library.org/news/secadv/20260127.txt
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Frequently Asked Questions
A security vulnerability is a weakness in software, hardware, or configuration that can be exploited to compromise confidentiality, integrity, or availability. Many vulnerabilities are tracked as CVEs (Common Vulnerabilities and Exposures), which provide a standardized identifier so teams can coordinate patching, mitigation, and risk assessment across tools and vendors.
CVSS (Common Vulnerability Scoring System) estimates technical severity, but it doesn't automatically equal business risk. Prioritize using context like internet exposure, affected asset criticality, known exploitation (proof-of-concept or in-the-wild), and whether compensating controls exist. A "Medium" CVSS on an exposed, production system can be more urgent than a "Critical" on an isolated, non-production host.
A vulnerability is the underlying weakness. An exploit is the method or code used to take advantage of it. A zero-day is a vulnerability that is unknown to the vendor or has no publicly available fix when attackers begin using it. In practice, risk increases sharply when exploitation becomes reliable or widespread.
Recurring findings usually come from incomplete Asset Discovery, inconsistent patch management, inherited images, and configuration drift. In modern environments, you also need to watch the software supply chain: dependencies, containers, build pipelines, and third-party services can reintroduce the same weakness even after you patch a single host. Unknown or unmanaged assets (often called Shadow IT) are a common reason the same issues resurface.
Use a simple, repeatable triage model: focus first on externally exposed assets, high-value systems (identity, VPN, email, production), vulnerabilities with known exploits, and issues that enable remote code execution or privilege escalation. Then enforce patch SLAs and track progress using consistent metrics so remediation is steady, not reactive.
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