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MCP Python SDK: Unbounded Session Accumulation in StreamableHTTP Transport Enables Resource Exhaustion

Moderate severity GitHub Reviewed Published Sep 30, 2026 in modelcontextprotocol/python-sdk • Updated Oct 15, 2026

Package

pip mcp (pip)

Affected versions

>= 1.8.0, < 1.30.0
>= 2.0.0, < 2.2.0

Patched versions

1.30.0
2.2.0

Description

Summary

In affected versions, a Streamable HTTP server in stateful mode (the default) never reclaimed session state:

  • sessions did not expire;
  • a client DELETE ended the session but left its entry registered;
  • a session whose first request was refused stayed registered with a running task.

Each session also kept its parsed initialize parameters, and the number of sessions was unlimited. A client that could reach the endpoint could grow server memory without bound using ordinary short requests; only a restart reclaimed it.

Am I affected?

Yes, if you serve MCP over Streamable HTTP in stateful mode and clients you do not fully trust can reach the endpoint. Stateful mode is the default for:

  • FastMCP (1.x)
  • MCPServer and Server.streamable_http_app() (2.x)
  • StreamableHTTPSessionManager

Affected versions: 1.8.0 through 1.29.1, and 2.0.0 through 2.1.1.

Not affected:

  • servers on 1.12.0 or later passing stateless_http=True (no sessions are kept)
  • servers using only the stdio or SSE transports

Authentication limits who can open sessions, not how many a token holder can open.

Fix

Upgrade to mcp 1.30.0 (1.x) or 2.2.0 (2.x) or later. In those versions:

  • a session with no request in flight for session_idle_timeout seconds (default 1800) is closed and its ID then answers 404; open streams and in-progress requests keep it alive;
  • at most max_sessions sessions exist at once (default 10000); a request that would open another is answered 503;
  • a session is discarded as soon as it ends, whether by DELETE, expiry, or a refused opening request.

Both settings are keyword arguments on FastMCP(...) (1.x), MCPServer.run() / streamable_http_app() (2.x) and StreamableHTTPSessionManager; None disables them.

This bounds retention rather than eliminating it: a live session still holds its initialize parameters (up to roughly twice the 4 MiB body limit), and an initialize with invalid parameters still opens a session that expires like any other. On a small host, lower session_idle_timeout, max_sessions and max_request_body_size to fit.

If you cannot upgrade yet, pass stateless_http=True (1.12.0 or later) where you need no per-session state, or restrict who can reach the endpoint.

References

@maxisbey maxisbey published to modelcontextprotocol/python-sdk Sep 30, 2026
Published by the National Vulnerability Database Oct 14, 2026
Published to the GitHub Advisory Database Oct 15, 2026
Reviewed Oct 15, 2026
Last updated Oct 15, 2026

Severity

Moderate

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 v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability Low
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:L/SC:N/SI:N/SA:N

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.
(38th percentile)

Weaknesses

Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource. Learn more on MITRE.

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.

Missing Release of Resource after Effective Lifetime

The product does not release a resource after its effective lifetime has ended, i.e., after the resource is no longer needed. Learn more on MITRE.

CVE ID

CVE-2026-59951

GHSA ID

GHSA-84m7-p3x7-pcfv

Source code

Credits

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