CVE-2026-58108 in CodeChecker
Summary
by MITRE • 08/26/2026
The personal access token removal query selects from PersonalAccessTokenDB but filters on columns of Session, with no join between them. SQLAlchemy resolves that as an implicit cross join, so the filter does not constrain the delete to the calling user's own token in the way the code reads as intending. This way a user can delete all personal access tokens in the system.
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Analysis
by VulDB Data Team • 08/26/2026
The vulnerability described constitutes a critical authorization bypass rooted in flawed database query construction within an application utilizing SQLAlchemy ORM. The core technical flaw lies in the implementation of a deletion operation for Personal Access Tokens, where the developer intended to restrict the removal action exclusively to tokens belonging to the currently authenticated user. However, the underlying SQL query performs a selection from the PersonalAccessTokenDB table while applying filter conditions against columns associated with the Session entity without establishing an explicit join relationship between these two tables. In standard relational database operations, this absence of a defined foreign key or join condition forces the database engine to interpret the request as an implicit cross join, also known as a Cartesian product. This operation effectively pairs every row in the PersonalAccessTokenDB table with every row in the Session table, resulting in a massive intermediate result set that contains all possible combinations of tokens and sessions rather than filtering for specific user associations.
Because SQLAlchemy resolves this structural ambiguity by executing an implicit cross join, the subsequent filter conditions applied to the session columns do not successfully constrain the delete operation to the intended scope. Instead, since every token is paired with every active or historical session record in the database, the logical condition evaluating whether a token belongs to the calling user evaluates as true for all records due to the presence of at least one matching session row per token across the Cartesian product. Consequently, when the delete command is executed against this expanded result set, it does not remove only the tokens associated with the requesting user's identity but rather purges every personal access token stored in the system regardless of ownership. This represents a severe breakdown in object-level authorization controls where the application fails to enforce proper isolation between distinct users' data assets.
The operational impact of this vulnerability is catastrophic for system integrity and security posture. An attacker who obtains valid credentials or exploits any other vector to authenticate as a low-privilege user can trigger this endpoint to delete all personal access tokens across the entire platform. This action effectively invalidates authentication mechanisms for every active user, leading to widespread service disruption and potential data loss if those tokens were used for automated processes or critical administrative functions. Furthermore, depending on how the application handles token revocation cascades, deleting these tokens might inadvertently trigger secondary vulnerabilities such as denial of service against legitimate users who are suddenly locked out of their accounts. The ability to wipe all authentication credentials simultaneously undermines the fundamental principle of least privilege and demonstrates a complete failure in input validation regarding database query construction logic.
From a classification perspective, this vulnerability aligns with CWE-269 Improper Privilege Management as it allows an unauthorized actor to perform administrative-level data destruction through misconfigured access controls. It also relates closely to CWE-89 SQL Injection if the lack of proper join syntax is viewed broadly under improper query construction that leads to unintended side effects, though more accurately it falls under CWE-611 Improper Restriction of XML External Entity References or similar logic errors in ORM usage where implicit joins lead to data exposure or modification beyond intended boundaries. In terms of MITRE ATT&CK mapping, this behavior facilitates the Disruption via Defacement or Denial of Service techniques by allowing a single user account to degrade system availability for all other users. It may also be categorized under T1531 Accessing Cloud Infrastructure Data Storage if these tokens are used in cloud environments, representing an abuse of legitimate functionality that leads to significant operational compromise.
Mitigation strategies must focus on correcting the database query logic and enforcing strict ORM best practices. The primary fix involves explicitly defining a join between the PersonalAccessTokenDB table and the Session entity using SQLAlchemy's join method or relationship definitions based on foreign keys. This ensures that the filter conditions correctly correlate tokens with their specific owners, thereby restricting the delete operation to only those records where the token owner matches the authenticated user's identity. Additionally developers should implement explicit checks before executing bulk deletions to verify ownership of each targeted record rather than relying solely on query filters which can be ambiguous in complex ORM setups. Implementing unit tests that specifically target edge cases involving cross-table relationships and verifying that delete operations do not affect unrelated entities is essential for preventing regression. Regular security code reviews focusing on SQL generation patterns within the application layer will further reduce the risk of similar implicit join vulnerabilities arising from developer oversight or misunderstanding of database semantics.