Skip to content

Latest commit

 

History

History
127 lines (91 loc) · 9.18 KB

mitigations.md

File metadata and controls

127 lines (91 loc) · 9.18 KB

Mitigation Strategies Analysis for chroma-core/chroma

Mitigation Strategy: Authentication and Authorization (Chroma Server)

Mitigation Strategy: Authentication and Authorization (Chroma Server)

Description:

  1. Enable Authentication: If using Chroma in a client-server configuration, ensure authentication is enabled on the Chroma server itself. This is a configuration setting within Chroma.
  2. Strong Credentials: Use strong, unique passwords or API keys/tokens for client authentication to the Chroma server. Avoid default credentials. Configure these within Chroma's settings.
  3. Role-Based Access Control (RBAC): If Chroma supports it (future versions might), implement RBAC within Chroma to define different roles with specific permissions. If not directly supported, simulate RBAC through careful management of client-side access and query construction (see below).
  4. Regular Audits: Periodically review Chroma's user accounts and permissions (if applicable) to ensure they are still appropriate. This involves checking Chroma's configuration.

Threats Mitigated: * Unauthorized Access (Severity: High): Prevents unauthorized clients from connecting to the Chroma server. * Data Modification (Severity: High): Limits the ability of unauthorized clients to modify data or embeddings stored in Chroma. * Data Exfiltration (Severity: High): Restricts access to sensitive data stored in Chroma.

Impact: * Unauthorized Access: High impact; fundamental security control for the Chroma server. * Data Modification: High impact; protects data integrity within Chroma. * Data Exfiltration: High impact; limits data leakage from Chroma.

Currently Implemented: * Basic authentication using username/password is enabled in Chroma's configuration.

Missing Implementation: * No RBAC implemented within Chroma (relying on client-side controls). * No regular audits of Chroma's user accounts and permissions (if applicable).

Mitigation Strategy: Rate Limiting (Chroma Server)

Mitigation Strategy: Rate Limiting (Chroma Server)

Description:

  1. Chroma-Level Rate Limiting: If Chroma provides built-in rate limiting capabilities (check the server configuration and documentation), configure these limits directly within Chroma.
  2. Define Limits: Set rate limits based on the type of request (reads, writes, deletes) and expected usage patterns. Configure these limits within Chroma's settings.
  3. Monitor and Adjust: Continuously monitor Chroma's rate limiting effectiveness (if available through Chroma's monitoring features) and adjust limits as needed.

Threats Mitigated: * Denial of Service (DoS) (Severity: High): Prevents attackers from overwhelming the Chroma server with requests. * Resource Exhaustion (Severity: High): Protects Chroma's resources from being depleted. * Abuse (Severity: Medium): Limits the ability of users to abuse the Chroma server.

Impact: * DoS: High impact; essential for protecting the Chroma server against DoS. * Resource Exhaustion: High impact; prevents Chroma's resources from being depleted. * Abuse: Moderate impact; controls usage of the Chroma server.

Currently Implemented: * No rate limiting is currently implemented within Chroma.

Missing Implementation: * Chroma-level rate limiting is completely missing (if supported by the version in use). This is a significant vulnerability if Chroma offers this feature.

Mitigation Strategy: Query Complexity Limits

Mitigation Strategy: Query Complexity Limits

Description:

  1. Maximum Results: Enforce a limit on the number of results returned by a single query using Chroma's query parameters (e.g., the limit parameter in get() or query()).
  2. Maximum Distance/Similarity Threshold: Set limits on the acceptable distance or similarity threshold within Chroma's query parameters (e.g., where clause with distance constraints).
  3. Filter Complexity: Limit the complexity of filtering conditions within Chroma's query parameters (e.g., the number of AND or OR clauses in the where clause). This might require careful client-side construction of queries.
  4. Query String Length: If Chroma exposes a raw query string interface, limit the length of the query string that is sent to Chroma.
  5. Informative Error Messages: If Chroma returns error messages for exceeding complexity limits, ensure your application handles these gracefully.

Threats Mitigated: * Denial of Service (DoS) (Severity: High): Prevents attackers from crafting computationally expensive queries that could overload Chroma. * Resource Exhaustion (Severity: High): Limits Chroma's resource consumption by complex queries.

Impact: * DoS: High impact; protects Chroma from resource exhaustion attacks. * Resource Exhaustion: High impact; controls Chroma's resource usage.

Currently Implemented: * A maximum results limit (limit=100) is enforced when calling Chroma's query() function.

Missing Implementation: * No limits on distance/similarity thresholds within Chroma queries. * No limits on filter complexity within Chroma queries (relying on client-side validation, which is less effective). * No limits on query string length (if applicable to the Chroma interface used).

Mitigation Strategy: Outlier Detection (Post-Embedding, within Chroma)

Mitigation Strategy: Outlier Detection (Post-Embedding, within Chroma)

Description: 1. Leverage Chroma's Filtering: If Chroma provides built-in functions or filtering capabilities that can be used for outlier detection (e.g., range queries on embedding dimensions, nearest neighbor searches with distance thresholds), use these directly within Chroma queries. 2. Post-Processing of Chroma Results: If Chroma doesn't have direct outlier detection, retrieve embeddings from Chroma (using appropriate limits and filters) and perform outlier detection using the retrieved data. This is less efficient but still leverages Chroma's storage and retrieval. 3. Quarantine within Chroma: If outliers are detected, use Chroma's update or delete functionality to mark them as inactive or remove them from the active collection. This keeps the outlier management within the Chroma context.

Threats Mitigated: * Data Poisoning (Severity: Critical): Identifies and isolates potentially malicious embeddings stored in Chroma. * Embedding Manipulation (Severity: Critical): Detects embeddings within Chroma that have been altered or injected.

Impact: * Data Poisoning: Moderate to high impact; depends on how effectively Chroma's features can be used for outlier detection. * Embedding Manipulation: Moderate to high impact; helps identify and isolate manipulated embeddings within Chroma.

Currently Implemented: * Basic distance-based outlier detection is implemented by retrieving embeddings from Chroma and processing them externally.

Missing Implementation: * No direct use of Chroma's filtering capabilities (if any exist) for outlier detection. * No automated quarantining of outliers within Chroma.

Mitigation Strategy: Inference Attack Mitigations (Query-Level)

Mitigation Strategy: Inference Attack Mitigations (Query-Level)

Description:

  1. Access Control to Query Results (Chroma-Specific): Implement fine-grained access control at the query level. This means constructing Chroma queries that only retrieve data the user is authorized to see. This leverages Chroma's filtering capabilities (where clause) to enforce access control. This is crucial because it prevents the application from even accessing unauthorized data within Chroma.
  2. Audit Query Logs (If Chroma Provides): If Chroma provides query logging, regularly review these logs specifically looking for patterns that might indicate inference attacks.
  3. Data Minimization (Collection Design): When designing your Chroma collections, only store the minimum necessary data. Avoid storing unnecessary sensitive information within Chroma.

Threats Mitigated: * Inference Attacks (Severity: Medium to High): Reduces the risk of attackers inferring sensitive information from query results returned by Chroma.

Impact: * Inference Attacks: The impact depends on the granularity of access control implemented through Chroma queries. Fine-grained control is essential.

Currently Implemented: * Basic access control to query results based on user roles, implemented by modifying the where clause in Chroma queries.

Missing Implementation: * No regular auditing of Chroma's query logs (if available). * No formal data minimization policy applied to Chroma collection design.