GHSA-f5vp-w269-392g CVE-2026-55434 GO-2026-5921
Coder vulnerable to denial of service via unbounded request body in AI Bridge provider endpoints
Medium
Go
- Severity
- 6.5 / 10
- Medium · CVSS 3.1
- Exploit chance (EPSS)
- 0.55%
- Chance of exploitation in the next 30 days. Higher than 46.14% of scored vulnerabilities.
- Known exploited
- No
- Not in CISA's catalog
- Weakness
- CWE-770 Allocation of Resources Without Limits or Throttling
- Fix
2.34.2- Upgrade github.com/coder/coder/v2 to this version or later
Description
Summary
AI Bridge provider handlers read request bodies with io.ReadAll without a maximum size so an authenticated user with AI Bridge access could send an arbitrarily large body and exhaust memory.
Note: Exploitation requires authenticated access to the AI Bridge endpoints and the impact is limited to availability (denial of service).
Impact
An authenticated member-level user could POST a very large or chunked body to an AI Bridge provider endpoint such as /api/v2/aibridge/anthropic/v1/messages, growing heap memory until the operating system terminates the process. Because AI Bridge runs in-process with coderd, this crashes the entire control plane, including the API, workspace coordinator and DERP relay. It requires an authenticated user and the AI Bridge feature enabled.
Patches
The fix applies http.MaxBytesReader or an equivalent cap before reading provider and session request bodies. The affected AI Bridge provider endpoints exist only on the v2.33 and v2.34 lines. Earlier release lines are not affected.
The fix is available in the following releases:
| Release line | Patched version |
|---|---|
| 2.34 | v2.34.2 |
| 2.33 | v2.33.8 |
Workarounds
None.
Resources
- Fix: #26164
Credits
Coder would like to thank Anthropic's Security Team (ANT-2026-22443) for independently disclosing this issue!
Affected versions
Go
| Package | Vulnerable | Fixed in |
|---|---|---|
| github.com/coder/coder | all versions |
No fix yet |
| github.com/coder/coder/v2 | >= 2.34.0, < 2.34.2 |
2.34.2 |
| github.com/coder/coder/v2 | >= 2.33.0, < 2.33.8 |
2.33.8 |
| github.com/coder/coder/v2 | >= 2.33.0, < 2.33.8>= 2.34.0, < 2.34.2 |
2.33.82.34.2 |
How to fix
Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.
github.com/coder/coder/v2 Go → 2.34.2
- go
go get github.com/coder/coder/v2@v2.34.2 && go mod tidy
Severity breakdown
CVSS 3.1 6.5
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H
- Attack vector
- Network
- Attack complexity
- Low
- Privileges required
- Low
- User interaction
- None
- Scope
- Unchanged
- Confidentiality
- None
- Integrity
- None
- Availability
- High
Weakness
CWE-770: 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.
How to prevent it
- Requirements: Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
- Architecture and Design: Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
- Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
- Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
- Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
- Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
- Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
- Architecture and Design, Implementation: If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery. Ensure that all failures in resource allocation place the system into a safe posture.
- Operation, Architecture and Design: Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems. When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users. Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).
References
Advisories
Packages
Other links
Timeline
- Published
- Last updated by the source
- Latest EPSS score
Related advisories
| Advisory | Severity | Why it's related |
|---|---|---|
| GHSA-h58c-xccx-75m3 Coder: Stored HTML injection via unescaped ApplicationName and LogoURL appearance settings | Medium | Also affects github.com/coder/coder |
| GHSA-8fxq-53rx-ph5f Coder: Login endpoint user enumeration via timing-defense placeholder in password comparison | Medium | Also affects github.com/coder/coder |
| GHSA-qrwj-vh9x-gw5v Coder's workspace agent API insecure redirect handling allowed cross-agent file read and write | High | Also affects github.com/coder/coder |
| GHSA-5wg6-jmq2-53pw Coder's workspace app CORS origin check can be bypassed via UUID-based subdomain spoofing | Medium | Also affects github.com/coder/coder |
| GHSA-7qw2-f75v-62f7 Coder vulnerable to stored HTML injection via workspace agent logs in AgentLogLine component | Medium | Also affects github.com/coder/coder |
| GHSA-84rm-42xw-mx52 Coder's AI Bridge Proxy skips TLS certificate verification in default configuration | High | Also affects github.com/coder/coder |
| GHSA-wqxv-w64v-5wh6 Suspended Coder users retain access to AI Bridge LLM proxy endpoints | Medium | Also affects github.com/coder/coder |
| GHSA-jqj2-x4c5-jfxm Coder: Devcontainer recreate endpoint missing write authorization allows read-only roles to destroy containers | Medium | Also affects github.com/coder/coder |
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