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Aegra has cross-user run injection in /threads/{thread_id}/runs (IDOR)

High severity GitHub Reviewed Published Apr 30, 2026 in aegra/aegra • Updated May 14, 2026

Package

pip aegra-api (pip)

Affected versions

>= 0.9.0, < 0.9.7

Patched versions

0.9.7

Description

Impact

Aegra deployments running 0.9.0 through 0.9.6 with multiple authenticated users on a shared instance are vulnerable to a cross-tenant IDOR. Any authenticated user (User A), given another user's thread_id (User B), can:

  • Execute graph runs against User B's thread via POST /threads/{thread_id}/runs, POST /threads/{thread_id}/runs/stream, or POST /threads/{thread_id}/runs/wait
  • Read User B's full checkpoint state via the resulting run's output field
  • Inject arbitrary messages into User B's conversation history (persisted in B's checkpoint)
  • Hide their activity from User B's GET /threads/{thread_id}/runs listing because the run carries A's user_id

The streaming variant is worse — the first SSE event: values frame returns the entire prior messages array immediately on connection, no graph execution needed.

Thread IDs are UUIDs but leak through frontend URLs, server logs, observability traces, and shared links. Guessing is not required.

Patches

Fixed in 0.9.7. The three affected endpoints now perform an SQL-level user_id == authenticated_user.identity check before calling _prepare_run. When the thread exists but is owned by another user, the response is 404 Thread not found (matching the read-side pattern) to avoid leaking thread existence.

Workarounds

If upgrade is not immediately possible, register an @auth.on("threads", "create_run") handler that explicitly verifies thread ownership against the authenticated identity before allowing the operation. Without a handler, no built-in authorization runs on these write paths.

Example mitigation handler:

from langgraph_sdk import Auth

auth = Auth()

@auth.on("threads", "create_run")
async def enforce_thread_owner(ctx: Auth.types.AuthContext, value: dict):
    # Look up the thread, raise 404 if not owned by ctx.user.identity.
    # Implementation depends on your data layer.
    ...

Root cause

Aegra's authorization model delegates per-resource policy to user-defined @auth.on handlers. When no handler is registered, handle_event(...) returns None and the request proceeds (default-allow). Read endpoints in api/threads.py add a defense-in-depth user_id filter at the SQL layer, but the run-creation endpoints in api/runs.py skipped that filter. Result: out-of-the-box deployments without custom auth handlers were vulnerable.

Affected endpoints

  • POST /threads/{thread_id}/runs
  • POST /threads/{thread_id}/runs/stream
  • POST /threads/{thread_id}/runs/wait

Stateless variants (POST /runs, POST /runs/wait, POST /runs/stream) are NOT affected — they generate a fresh thread_id server-side and never accept a caller-supplied one.

Credits

  • @JoJoTheBizarre — discovered and reported the vulnerability with a precise reproducer (#336)
  • @victorjmarin and @jawhardjebbi — wrote the fix and added test coverage at unit, integration, and manual-auth e2e levels (#337)

Resources

References

@ibbybuilds ibbybuilds published to aegra/aegra Apr 30, 2026
Published to the GitHub Advisory Database May 7, 2026
Reviewed May 7, 2026
Published by the National Vulnerability Database May 14, 2026
Last updated May 14, 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 v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required Low
User interaction None
Vulnerable System Impact Metrics
Confidentiality High
Integrity High
Availability None
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:L/UI:N/VC:H/VI:H/VA:N/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.
(3rd percentile)

Weaknesses

Improper Authorization

The product does not perform or incorrectly performs an authorization check when an actor attempts to access a resource or perform an action. Learn more on MITRE.

Authorization Bypass Through User-Controlled Key

The system's authorization functionality does not prevent one user from gaining access to another user's data or record by modifying the key value identifying the data. Learn more on MITRE.

CVE ID

CVE-2026-44504

GHSA ID

GHSA-m98r-6667-4wq7

Source code

Credits

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