CVE-2026-82076: 
MongoDB 脆弱性の分析と軽減

CVE-2026-82076 is an integer overflow vulnerability in the query planning component of MongoDB Server that allows an authenticated user with ordinary database-level read/write privileges to trigger unbounded memory consumption, resulting in a denial of service. Disclosed on September 8, 2026, the vulnerability affects MongoDB Server versions 7.0.0 through 7.0.40, 8.0.0 through 8.0.29, 8.2.0 through 8.2.12, 8.3.0 through 8.3.8, and pre-release builds 9.0.0-alpha0 and 9.0.0-alpha1. It carries a CVSS v3.1 base score of 6.5 (Medium) and a CVSS v4.0 base score of 7.1 (High) (Feedly, MongoDB Jira).

The root cause is an integer overflow (CWE-190, mapped to CAPEC-92: Forced Integer Overflow) in MongoDB's query planning subsystem, which allows a crafted query to bypass an internal resource limit that is intended to cap memory usage during query planning. When the overflow occurs, the server allocates memory without bound until the process is terminated by memory exhaustion. Exploitation requires only low-privilege, authenticated network access — no special configuration or elevated permissions are needed beyond standard database read/write access (Feedly, MongoDB Jira).

Successful exploitation causes the MongoDB server process to terminate due to uncontrolled memory exhaustion, resulting in a denial of service that affects all databases hosted on the compromised node. There is no confidentiality or integrity impact — the vulnerability is purely an availability concern. Because a single node failure can disrupt all databases it serves, deployments without redundancy (e.g., replica sets or sharded clusters) face complete service outages (Feedly).

No public proof-of-concept exploit code has been observed, and there is no evidence of in-the-wild exploitation as of the time of disclosure (Feedly). The EPSS score is approximately 0.316%, indicating a low probability of exploitation in the near term. The vulnerability is not listed in the CISA Known Exploited Vulnerabilities (KEV) catalog. NVD's SSVC assessment classifies the vulnerability as non-automatable with no known exploitation (Feedly).

1. Reconnaissance: Identify MongoDB Server instances running vulnerable versions (7.0.0–7.0.40, 8.0.0–8.0.29, 8.2.0–8.2.12, 8.3.0–8.3.8) using network scanning tools such as Shodan, Censys, or nmap targeting default MongoDB port 27017.
2. Authentication: Obtain or use existing low-privilege credentials with ordinary database-level read/write access to the target MongoDB instance.
3. Craft malicious query: Construct a specially crafted query designed to trigger the integer overflow in the query planning component, causing the internal memory resource limit to be bypassed.
4. Submit query: Send the crafted query to the MongoDB server via the standard MongoDB wire protocol (e.g., using the mongo shell, a MongoDB driver, or a direct TCP connection).
5. Trigger DoS: The server's query planner processes the malicious query, overflows the integer counter, and begins consuming memory without bound until the server process is terminated, taking all hosted databases offline (Feedly, MongoDB Jira).

• Network: Unusual or repeated query traffic on MongoDB port 27017 from authenticated but low-privilege accounts, particularly queries with abnormal complexity or structure.
• Logs: MongoDB server logs (mongod.log) showing sudden process termination with out-of-memory errors or signals (e.g., SIGKILL, OOM killer entries in system logs) immediately following query execution.
• Process/System: Rapid, unbounded growth in mongod process memory consumption visible via system monitoring tools (e.g., top, htop, ps); OS-level OOM killer events referencing the mongod process in /var/log/syslog or /var/log/messages.
• Availability: Unexpected MongoDB service restarts or crashes correlated with specific query submissions from a particular authenticated user or application account (Feedly).

MongoDB has released patched versions addressing this vulnerability: 7.0.41, 8.0.30, 8.2.13, and 8.3.9. Organizations should upgrade to one of these versions immediately. As interim mitigations, consider implementing network-level access controls to restrict which clients can connect to MongoDB instances, enforcing the principle of least privilege for database accounts, and monitoring server memory usage with alerting for abnormal consumption patterns during query execution (Feedly, MongoDB Jira, Tenable).