PatchFirst · Latest vulnerabilities
Vulnerabilities published for mem0ai in the last 30 days: 1. Listed in the KEV catalogue: 0.
Vulnerabilities: 5
mem0 0.1.117 before 1.0.8 contains an sql injection vulnerability in mem0/vector_stores/databricks.py that allows attackers to inject SQL by influencing stored memory content. Attackers can supply crafted memory text, metadata, or message names that reach unescaped insert() and update() string interpolation to execute injected SQL on the configured Databricks SQL warehouse.
The mem0 1.0.0 server lacks authentication and authorization controls for its memory creation API endpoint (POST /memories). The endpoint allows unauthenticated users to submit arbitrary memory records without verifying their identity or permissions. A remote attacker can exploit this by sending unauthenticated POST requests to create malicious or spoofed memory entries in the database, leading to unauthorized data injection and potential data pollution.
The mem0 1.0.0 server lacks authentication and authorization controls for its memory deletion API endpoint (DELETE /memories). The endpoint allows unauthenticated users to delete memory records by specifying arbitrary user identifiers (e.g., user_id, run_id, agent_id) in the request query parameters. A remote attacker can exploit this by sending unauthenticated DELETE requests to erase memory data for any user, leading to unauthorized data loss and denial of service.
The mem0 1.0.0 server lacks authentication and authorization controls for its memory management API endpoints. Critical functions such as updating memory records (PUT /memories/{memory_id}) are exposed without any verification of the requester's identity or permissions. A remote attacker can exploit this by sending unauthenticated requests to modify, overwrite, or delete arbitrary memory records, leading to unauthorized data manipulation and potential data loss.
A vulnerability was found in mem0ai mem0 up to 1.0.11. This affects the function pickle.load/pickle.dump of the file mem0/vector_stores/faiss.py. Performing a manipulation results in deserialization. It is possible to initiate the attack remotely. The exploit has been made public and could be used. The patch is named 62dca096f9236010ca15fea9ba369ba740b86b7a. Applying a patch is the recommended action to fix this issue.
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