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+# TiKV Security Self-Assessment
+
+## Table of contents
+
+* [Metadata](#metadata)
+ * [Security links](#security-links)
+* [Overview](#overview)
+ * [Background](#background)
+ * [Architecture](#architecture)
+ * [Actors](#actors)
+ * [Actions](#actions)
+ * [Goals](#goals)
+ * [Non-goals](#non-goals)
+* [Self-assessment use](#self-assessment-use)
+* [Security functions and features](#security-functions-and-features)
+* [Project compliance](#project-compliance)
+* [Secure development practices](#secure-development-practices)
+* [Security issue resolution](#security-issue-resolution)
+* [Appendix](#appendix)
+* [STRIDE Threat Model](#stride-threat-model)
+* [Questions about potential vulnerabilities](#questions-about-potential-vulnerabilities)
+* [Suggested action items](#suggested-action-items)
+
+## Metadata
+| | |
+| -- | -- |
+| Software | [TiKV](https://github.com/tikv/tikv/tree/master) |
+| Security Provider | No |
+| Languages | Rust, Java, Go, and C |
+| SBOM |Link to the dependencies file: [Cargo.toml](https://github.com/tikv/tikv/blob/master/Cargo.toml) |
+| | |
+
+### Security links
+
+
+| Doc | url |
+| -- | -- |
+| Security file | https://github.com/tikv/tikv/blob/master/security/Security-Audit.pdf |
+| Default and optional configs | https://tikv.org/docs/3.0/tasks/configure/security/ |
+
+## Overview
+**TiKV (Ti Key-Value)**
+
+TiKV is an open-source, distributed, and transactional key-value database designed without heavy dependencies on existing distributed file systems. TiKV is scalable, low latency, and an easy to use key-value database, and it is optimized for petabyte-scale deployments.
+
+TiKV is inspired from Titanium (‘***Ti***’), as the creators kept the element’s property in mind. ‘***KV***’ stands for the ‘key-value’ combination in reference to the databases where it is primarily used.
+
+### Background
+
+Key-value databases are optimized for fast data retrieval. They offer high performance for read/write operations, making them ideal for applications that require rapid access to data.
+
+TiKV is part of the Cloud Native Computing Foundation and created by PingCAP; it features ACID-compliant transactional APIs and ensures data consistency and high availability through the Raft Consensus Algorithm. The aim of the project is to provide a solution similar to Google Spanner and HBase, but with a focus on simplicity and ease of use for massive datasets.
+
+### Architecture
+
+
+
+* **Layers**
+ - OS Layer Storage Engine (RocksDB)
+ - Consensus Model
+ - Transaction (implements MVCC = multiversion concurrency control and distributed transactions)
+ - KV API
+ - Clients (using the gRPC protocol to connect to TiKV)
+
+* **Storage Engine**
+ - Uses [RocksDB](https://rocksdb.org/)
+ - High Read/Write Performance
+ - Easy to embed in Rust (TiKV is written in Rust)
+ - Stable
+
+* **Consensus Model**
+
+
+
+ * Raft Consensus Algorithm
+ - Client reads/writes to leader node
+ - Leader node replicates client requests to follower nodes
+ - The transaction is successful if the majority of the nodes (including leader and follower nodes) have fulfilled the client request
+ - If the leader node fails, then the up-to-date follower node becomes the leader
+ - There is a minimum of three nodes in a TiKV cluster
+ - As long as the majority of nodes are alive, the whole cluster is available
+
+ * TiKV uses Range Sharding as opposed to Hash Sharding, which is used by other systems
+
+
+
+ * Range Sharding is better when scaling
+
+ * TiKV brings together Replication (Raft Consensus Protocol) and Sharding (Range Sharding)
+
+
+
+ * When Scaling (i.e. adding extra nodes), the nodes are balanced and the leader of one node, becomes the leader of the new node
+
+* **The Placement Driver**
+ - The Placement Driver Cluster stores “Region Information,” which the client can use to know which node to access
+ - The Placement Driver is “Highly Available”
+
+* **Client**
+ - The client uses the [gRPC](https://grpc.io/) protocol to interface with Placements Drivers and TiKV nodes
+
+
+
+### Actors
+
+* **Clients**
+* **TiKV Instance**
+ - Data Regions (within TiKV Nodes)
+* **Placement Driver**
+ - TimeStamp Oracle (within Placement Driver)
+
+### Actions
+
+* **Clients**
+ - TiKV provides two types of APIs for developers: the Raw Key-Value API and the Transactional Key-Value API
+* **TiKV Instance**
+ - Each instance acts isolated from every other node
+ - Data is distributed across TiKV instances via the Raft Consensus Algorithm
+ - Data Regions (within TiKV Nodes)
+ - This is the basic unit of key-value data movement
+ - Each Region is replicated to multiple Nodes, and multiple replicas form a Raft group
+* **Placement Driver**
+ - The cluster manager of TiKV periodically checks replication constraints to balance load and data automatically across nodes and regions in a process called auto-sharding
+ - TimeStamp Oracle (within Placement Driver)
+ - Plays a significant role in the Percolator transaction model, where every transaction requires contacting the Oracle at least twice and proper scalability
+
+### Goals
+
+* TiKV clients let you connect to a TiKV cluster and use raw (simple get/put) API or transaction (with transactional consistency guarantees) API to access and update your data. TiKV clients interact with PD and TiKV through gRPC
+* Scalability and consistency due to data being shared and replicated across multiple nodes (up to petabytes)
+* Ensure data confidentiality and integrity in transit and at rest, using TLS
+* Guarantee ACID properties for transactions to prevent data corruption
+* Externally consistent distributed transactions to operate over multiple Key-Value Pairs
+* Develop and maintain sophisticated access control systems to manage permissions effectively for different users and services interacting with TiKV
+* Ensure compatibility and integration with widely used cloud-native security tools and platforms for seamless deployment in various environments
+* TiKV adopts MVCC (Multiversion Concurrency Control) which offers an extra layer of security in data management by maintaining multiple versions of data records. This approach helps to prevent conflicts and inconsistencies in a distributed environment where concurrent transactions occur
+
+
+### Non-goals
+* Not supposed to be a relational database (No SQL)
+* Does not specifically implement features which compromise performance without clear security benefits
+* Perfect security is not a goal of TiKV; the aim should be to mitigate risk to acceptable levels as perfect security is unattainable
+* Does not address end-user security, such as password manager or client side security, which are outside the database’s control
+* Does not attempt to solve external network security issues that are beyond the scope of TiKV
+
+## Self-assessment use
+
+This self-assessment is created by the TiKV team to perform an internal analysis of the
+project's security. It is not intended to provide a security audit of TiKV, or
+function as an independent assessment or attestation of TiKV's security health.
+
+This document serves to provide TiKV users with an initial understanding of
+TiKV's security, where to find existing security documentation, TiKV plans for
+security, and general overview of TiKV security practices, both for development of
+TiKV as well as security of TiKV.
+
+This document provides the CNCF TAG-Security with an initial understanding of TiKV
+to assist in a joint-assessment, necessary for projects under incubation. Taken
+together, this document and the joint-assessment serve as a cornerstone for if and when
+TiKV seeks graduation and is preparing for a security audit.
+
+
+## Security functions and features
+
+* **Critical Security Functions and Features:**
+ - ***Transport-Layer Security (TLS)***: This is necessary for encrypted communication between TiKV nodes. This ensures the integrity and confidentiality of data in transit. TiKV uses OpenSSL to implement its TLS encryption.
+ - ***Programming Language (Rust)***: TiKV is written in Rust, a memory-safe language. This can be important to avoid memory leaks, buffer overflows, race conditions, etc.
+ - ***Timestamps and MVCC (Multiversion Concurrency Control)***: While this may not necessarily be thought of as a security feature, this is important because it helps maintain data consistency and integrity in a distributed environment.
+ - ***Raft Consensus Algorithm***: As with MVCC, although this may not necessarily be considered a security feature, this ensures fault tolerance and maintains availability of the data, in addition to consistency across distributed nodes.
+ - ***Authentication***: This is a fundamental principle to control access to TiKV clusters. Without authentication, there is no way of ensuring that only authorized users are interacting with node clusters.
+
+* **Relevant Security Functions and Features:**
+ - ***Role-Based Access Control***: Although Role-Based Access Control (RBAC) itself can be considered a critical security feature, specific roles and associated privileges can be defined and configured based on the security policy and needs of the organization.
+ - ***Encryption Configuration***: Although there is no built-in [on-disk encryption](https://tikv.org/docs/4.0/tasks/configure/security/), it is possible to pair TiKV with encryption at rest, which can provide an extra layer of security by protecting data on the disk.
+ - ***Cluster Security***: Certain network security features, such as firewalls, can be configured by an organization depending on its security policies and needs in order to resrict access to TiKV nodes and ensure communication between trusted entities.
+ - ***TLS Certificate Management***: Although TLS is a critical security feature, depending on the infrastructure of the organization, TiKV allows for the [configuration](https://tikv.org/docs/6.1/deploy/configure/security/) of TLS certificates and keys for TiKV services, Placement Driver Services, and/or TiKV Clients.
+ - ***TiKV Backup and Restore Configurations***: TiKV Backup & Restore ([TiKV-BR](https://tikv.org/docs/dev/concepts/explore-tikv-features/backup-restore/)) is a command-line tool for distributed backup and restoration of TiKV cluster data. Certain aspects of a TiKV backup can be configured including use of a checksum and use of TLS.
+
+
+
+## Project compliance
+
+Although TiKV does not provide explicit documentation regarding its compliance with specific regulations, it adheres to general best practices in security as an open-source distributed database. Although initially developed for the Chinese market, TiKV's documentation does not explicitly address its compliance with Western regulations like GDPR and HIPAA. The documentation of project compliance can potentially expedite the process of adoption.
+
+## Secure development practices
+
+For testing, TiKV uses regression tests, performance tests, ChaosMesh, and models their algorithms utilizing TLA+. TiKV uses Cargo as a universal project tool, and split tests into test modules in respective code files. Among the fuzzing libraries used are LLVM's libfuzzer, AFL and Google's Honggfuzz; however, tests do not run in an automated fashion.
+
+The TiKV project utilizes persistent open groups which each focus on a part of the TiKV project; teams and members provided in the teams folder for each individual project. Each team consists of reviewers, committers, and maintainers:
+* **Reviewers**: Responsible for contributions and code review
+* **Committees**: Granted write access and usually responsible for certain areas of the project
+ - Each commit message must contain a “Signed-off-by” line for Developer Certificate of Origin
+* **Maintainers**: Responsible for moderating the discussions, managing project release, and proposing new committers or maintainers
+
+In addition, there is a separate infrastructure team, not responsible for the team decision-making process, but that helps on applying the decision. The current list of infrastructure members is provided with their emails and githubs on the TiKV Governance page.
+* **Infrastructure team**: Responsible for setting administration, security, and supporting the existing teams
+
+**Voting**
+* Decisions regarding the project are made by votes on the primary project community repository.
+* Votes are indicated via pull requests under the votes folder.
+* Positive votes require no explanation, while vetoes (negative votes) must have an explanation.
+* Required vote counts can vary based on the decision but typically require at least 2 positive votes.
+
+* Internal Communication: Slack
+
+ * Inbound Communication: Twitter, Blog, Reddit, Stack Overflow
+
+* Outbound Communication: None
+
+**Ecosystem**
+* At the time of writing, there are currently four client drivers: Go, Java, Rust, and C
+ - The Go client is the only stable client
+ - The Java and Rust clients are considered unstable
+ - The C client is currently in early development
+
+TiKV provides two separate clients: Raw and Transactional
+* ***Raw***: A lower-level key-value API for interacting directly with individual key-value pairs
+* ***Transactional***: A higher level key value API that provides ACID semantics
+
+## Security issue resolution
+
+***Note:*** When looking for methods of security issue resolution, there was no easily accessible area to discuss each protocol. This could potentially lead to mishaps like major security vulnerabilities being publicly shown as issues
+
+* Bug Fixes or documentation improvement can be implemented via a normal Github Pull Request workload
+* To contribute “substantial changes”, a RFC (request for comments) document provides a consistent and controlled path for new features to enter the project
+ - RFCs must provide summary, motivation, detailed design, drawbacks, alternative, and unanswered questions
+* To report a vital security vulnerability, an email should be sent to the TiKV-security group (tikv-security@lists.cncf.io), and encrypted using the public PGP key
+ - Disclosure Policy:
+ - The received security vulnerability report shall be handed over to the security team for follow-up coordination and repair work.
+ - After the vulnerability is confirmed, a draft Security Advisory will be created on Github that lists the details of the vulnerability.
+ - Invite related personnel to discuss the fix.
+ - Fork the temporary private repository on Github, and collaborate to fix the vulnerability.
+ - After the fixed code is merged into all supported versions, the vulnerability will be publicly posted in the GitHub Advisory Database.
+
+## Appendix
+
+***Known Issues Over Time***
+
+* **Outdated Library Versions**: Some libraries used in TiKV were outdated and not actively maintained, posing a security risk. This issue highlighted the need for better patch management and attention to third-party dependencies.
+* **Database Encryption**: While the TiKV database encryption was evaluated, it was found to be using a basic XOR method, not yet production-ready. However, according to PingCAP, it provides information about the encryption support in TiDB components. In TiKV, it supports encryption at rest, and it allows TiKV to transparently encrypt data files using AES or SM4 in CTR mode.
+* **Codebase TODOs**: A large number of TODO blocks in the TiKV source code indicated incomplete functionalities, requiring further evaluation and integration to the project’s issue tracker.
+* **Fuzz Testing**: The implemented fuzzing tests were not properly run or evaluated at the time of the assessment, signaling a need for improvement in this area.
+* **Dependency Scanner Disabled**: The integrated dependency scanner was disabled due to a non-updated dependency, leading to potential security risks from unmonitored dependencies.
+* **Lack of Bug Bounty Program**: While not a direct issue, a 2020 security audit suggested that implementing a bug bounty program could be beneficial for TiKV.
+* **High Apply Wait Tail Latency**: There was an issue with high latency in the apply wait tail, affecting performance.
+* **Performance regression**: A specific commit caused a 3-5% performance regression under certain workloads.
+* **False Positive in Slow Score**: This issue prevented the adoption of TiKV in production environments due to false positives in slow score measurement.
+* **Inconsistent Store Size After Enabling Titan**: Store size did not stabilize after enabling the Titan component.
+* **SST Importer Cleaning Requirement**: The SST Importer needed to clean the SST if no key-value needed to be saved and rewritten.
+* **CPU Usage of Snapshot-Worker Thread**: An enhancement was requested to reduce the CPU usage of this thread to prevent it from blocking scheduling.
+* **Slow Store Check Leader**: This bug potentially affected the ability of a store to advance resolve_ts.
+* **Titan Configuration Tuning**: This was listed as an enhancement issue to optimize the configuration of the Titan engine.
+* **Different Store Size Among Nodes After Enabling Titan**: There were issues with varying store sizes among TiKV nodes after Titan was enabled.
+* **TiKV Out of Memory (OOM)**: There were reported instances of TiKV running out of memory.
+* **Not All TiKV Clients Offer The Same Encryption**: According to TiKV's Security Configuration page, the TiKV Java Client does not currently support TLS.
+
+
+***CII Best Practices***
+ > A CII Best Practice is a process or method that, when executed effectively, leads to enhanced project performance. TiKV has many practices that seem to fulfill this concept.
+ * **Change Management**: TiKV, like many open-source projects, involves changes in code, features, and security practices. Effective change management is crucial in the particular context for ensuring stable and secure updates to the software.
+* **Risk Management**: The process of identifying, assessing, and managing risks is fundamental in developing software, especially a database like TiKV. This aligns with the CII best practices of project risk management, where potential impacts are evaluated to mitigate risks.
+* **Quality Management**: TiKV’s commitment to maintaining high-quality program and efficient processes represents the CII best practices of quality management. This encompasses activities to improve efficiency and compliance, important for projects like TiKV which is widely used in various industries.
+* **Lessons Learned**: Continuous improvement in software development is the key to achieve CII Best Practices. It is also important to keep track of its previous issues and bugs, and learn from its past experiences. TiKV has done a great job of that.
+
+
+***Case Studies***
+
+* **JD Cloud and AI** – A scalable database was required by cloud computing provider JD Cloud & AI to store metadata for its Object Storage Service (OSS). The metadata was exceeding the capacity of their MySQL database at an alarming rate. A globally ordered key-value store with the capacity to store enormous quantities of data was necessary. They decided to utilize TiKV following a scaled evaluation of their alternatives. TiKV is highly proficient in managing extensive datasets and offers support for petabyte-scale deployments. TiKV satisfied the performance, scalability, and defect tolerance criteria set forth by JD Cloud & AI after thorough testing. The application from TiKV has a latency of 10ms and a QPS of over 40,000. It has substituted MySQL as the metadata repository for their OSS. As of now, the principal database utilized by JD Cloud & AI for storing OSS metadata is TiKV.
+
+* **SHAREit Group - SHAREit**, a widely used global content and advertising platform, aimed to improve their recommendation systems. Their focus was on achieving lower latency and an efficient SQL interface. The company chose to use TiKV for storing data online and interacting with their recommendation system. In addition, they have a plan to incorporate TiDB, which is an open-source HTAP database. This integration will allow them to use online machine learning, which means they can continuously enhance their recommendations by providing online training. TiKV and TiDB have successfully met their requirements for handling a large number of simultaneous write operations and providing a SQL interface. This has resulted in a simplified architecture for these systems. By adopting open source, engineers have been able to significantly decrease the amount of time they spend on feature engineering. For reference, this task took up around 50% of their time, but now it has been reduced to 25% or even less. SHAREit has improved its architecture and AI workflow for recommendations by adopting TiKV and TiDB and has resulted in a more efficient and streamlined process.
+
+
+Deploys TiKV with TiDB:
+
+* **Hulu** a popular video-streaming service, adopts TiKV with TiDB into their platform. There isn't a lot of detailed information about how Hulu specifically deploys TiKV and TiDB. However, based on the general understanding of TiKV, it is known that TiKV is highly capable at managing distributed storage, while TiDB can handle SQL processing and transactions. Hulu could utilize it to store and organize large quantities of metadata associated with their video library and user interactions. TiKV lacks SQL interface and transactional support, so TiDB serves as a provider for these features. Hulu benefits from the combination of TiKV and TiDB because they provide a data infrastructure that is fast, scalable, and reliable. This enables Hulu to efficiently deliver content and recommendations to their audience.
+
+***Related Projects / Vendors***
+
+**Company: PingCAP; Offering: TiDB Cloud; Industry: DBaas.**
+PingCAP is the company behind the open-source TiKV project and supplies continuous development of the project. TiDB Cloud is a database-as-a-service (DBaas) provided by PingCAP. It is built using TiKV and TiDB technologies. It offers fully-managed clusters of the open source TiKV database in the cloud. TiDB Cloud manages various operational tasks such as provisioning, upgrades, scaling, monitoring, and ensuring high availability. The main difference is that some users may prefer the convenience of TiDB Cloud as a service to the responsibility of administering their own TiKV environment. Overall, TiDB Cloud is intended for utilization by users who desire to operate it locally or as a service. Both projects give users the opportunity to leverage PingCAP's innovative technology.
+
+## STRIDE Threat Model
+| STRIDE Element | Access Controls | Password Protection | Raft Consensus Algorithm | MVCC in TiKV | RocksDB Storage Engine | TiKV Clients | Placement Driver | Timestamp Oracle | Transport-Layer Security (TLS) | Programming Language (Rust) | Authentication |
+|-----------------------------------|-------------------------------------------------------------------------------|-----------------------------------------------------------------------------|-----------------------------------------------------------------------------|-----------------------------------------------------------------------------|------------------------------------------------------------------------------|-----------------------------------------------------------------------------|------------------------------------------------------------------------------|------------------------------------------------------------------------------|-----------------------------------------------------------------------------|------------------------------------------------------------------------------|------------------------------------------------------------------------------|
+| Spoofing Identity | Attackers could impersonate authorized users to gain access to TiKV nodes and PD. | Weak password protocols can be exploited to gain unauthorized access. | Falsifying identity as a leader node could disrupt consensus. | Spoofing transactions to appear as legitimate could enable unauthorized actions. | | Impersonating a legitimate client could allow unauthorized access to TiKV nodes. | Spoofing the Placement Driver could disrupt TiKV’s data management and routing. | Spoofing timestamp requests can lead to incorrect time assignments for transactions. | Intercepting TLS certificates could enable attackers to impersonate TiKV nodes. | | Impersonating an authenticated user can grant unauthorized access to sensitive functions. |
+| Tampering | Tampering with access control settings could weaken restrictions. | Attackers could alter authentication data or mechanisms. | Tampering with data replication processes can corrupt data consistency. | Tampering with timestamps could cause data inconsistencies or conflicts. | Altering RocksDB configurations or data could compromise data integrity. | Tampering with client applications can lead to malicious data insertion or alteration. | Tampering with PD’s metadata can lead to incorrect data placement or loss. | Manipulating timestamps can cause inconsistencies and conflicts in transaction ordering. | Tampering with TLS configurations can compromise secure communication. | Exploiting language-specific vulnerabilities, though less likely in Rust, can lead to data tampering. | Altering authentication data or mechanisms can lead to unauthorized system access. |
+| Repudiation | If audit trails are poor, malicious activities may go unrecorded, denying wrongdoing. | Lack of secure audit logs could prevent tracking unauthorized access changes. | Without proper logging, changes made to the consensus process might not be traceable. | Untraceable transactions due to poor logging could lead to repudiation of actions. | Without proper audit logs, unauthorized modifications in RocksDB might go unnoticed. | Clients could deny performing actions if actions are not properly logged. | Lack of auditing can make it difficult to trace unauthorized changes in PD. | Lack of traceability for timestamp issuance could enable denial of transaction manipulation. | Failure to log TLS configuration changes could allow unauthorized alterations to go unnoticed. | Rust's safety features reduce the likelihood of untraceable changes in the codebase. | Failure to log authentication attempts could allow unauthorized activities to be denied. |
+| Information Disclosure | Unauthorized access could lead to exposure of sensitive data. | Insufficient password protection might reveal user credentials. | Intercepting communications could reveal sensitive replicated data. | Unencrypted timestamps could reveal transaction times and patterns. | Vulnerabilities in third-party dependencies could lead to data leaks. | Compromised clients could leak sensitive data stored in TiKV. | Gaining access to PD can reveal critical metadata about data distribution. | Access to timestamping information could expose transaction patterns and timings. | Compromised TLS can lead to exposure of data in transit between nodes. | | |
+| Denial of Service | Overloading access control mechanisms could lead to service disruptions. | Repeated password attempts or protocol abuse could disrupt service. | Disrupting the consensus process can lead to denial of service. | Conflicts or faulty timestamping can lead to transaction processing delays. | Exploiting RocksDB vulnerabilities could slow down or halt data operations. | Overloading clients or exploiting vulnerabilities can disrupt their interaction with TiKV. | Overloading or disrupting PD can significantly impact data availability and cluster operations. | Overloading the Timestamp Oracle can delay or prevent timestamp issuance, disrupting transactions. | Disrupting TLS can block or slow down secure communication, affecting service availability. | | |
+| Elevation of Privilege | Gaining unauthorized access could lead to elevated privileges within the system. | Accessing accounts with higher privileges could lead to control over critical functions. | An attacker could gain control over data flow and decision-making by becoming a malicious leader. | Altering timestamps could grant unauthorized data access or modifications. | Exploiting vulnerabilities could lead to unauthorized access or control over data storage. | Accessing elevated privileges through client exploitation can lead to broader system compromise. | Controlling PD could grant significant control over the cluster’s operational aspects. | Manipulating the timestamping process could give undue advantage or access to certain transactions. | Compromised TLS could be exploited to gain access to encrypted communications, leading to privileged information access. | Exploiting rare vulnerabilities in Rust could lead to unauthorized system access. | |
+
+
+
+## Questions about potential vulnerabilities
+
+**Potential vulnerabilities in Key-Value Database Systems:**
+
+* Are there proper access controls that restrict unauthorized access to TiKV nodes and Placement Drivers by potentially malicious clients?
+* How safe are password protection methods (two-factor authentication)?
+
+**Potential vulnerabilities related to the Raft Consensus Algorithm:**
+
+* Are there proper integrity checks in place as the Leader Node is copying the client’s read/writes to the follower nodes?
+* Raft Consensus Algorithm could potentially be exploited via a Byzantine-control attack. If a malicious node is voted as leader, what does TiKV do to protect the rest of the Raft group?
+
+**Potential vulnerabilities related to Multiversion Concurrency Control (MVCC) used in TiKV:**
+
+* Is there any way to tamper with the timestamps in TiKV transactions?
+ - Transaction timestamps are stored in the metadata associated with each key-value pair
+ - If there is a conflict, i.e. two transactions trying to write to modify the same key, then only one transaction can be completed successfully, while others have to be retried.
+ - To prevent conflicts, TiKV uses locks to control key access.
+ - In theory, these timestamps are **not** encrypted, so the security of TiKV is contingent upon the security measures implemented at higher and lower levels (higher – Application level; lower – RocksDB)
+
+**Potential vulnerabilities related to RocksDB, TiKV’s storage engine:**
+* RocksDB may have vulnerable third-party dependencies, so if RocksDB has them, so does TiKV potentially.
+* RocksDB does not support Data-at-Rest encryption (DARE), so does this affect the layers above?
+* In fact, RocksDB does not have any built-in encryption features...
+
+**Potential vulnerabilities related to TiKV clients:**
+* A compromised client could potentially get unencrypted access, which would be made even worse due to an unencrypted disk?
+
+**Potential vulnerabilities related to Placement Driver:**
+* Placement Driver is responsible for storing all the metadata. If you control the Placement Driver could you affect availability or shut down the entire system?
+* How vulnerable is the placement driver?
+
+**Potential vulnerabilities related to Timestamp Oracle:**
+* How can the Timestamp Oracle meet excessive demand without scaling to multiple nodes (in large projects)
+* Timestamp Oracle is unable to be scaled up to multiple nodes
+* When the current Raft leader fails, there is a gap wherein the system cannot allocate a timestamp before a new leader has been elected. Can an attacker exploit this?
+
+## Suggested action items
+
+Although we were not able to receive feedback from the TiKV project maintainers (at the time of writing), we have formulated several action items related to our understanding of TiKV and its potential vulnerabilities:
+
+**Access Controls for TiKV Nodes and Placement Drivers**
+* Mutual TLS Authentication: Enforce mutual TLS (Transport Layer Security) for all communications between clients and TiKV nodes, ensuring that both parties are authenticated.
+
+**Password Protection and Authentication**
+* Adopt Advanced Authentication Mechanisms: Implement certificate-based authentication or integrate with identity providers that support OAuth2 or OpenID Connect, in addition to two-factor authentication.
+* Automated Credential Rotation: Implement automated systems for rotating credentials and keys at regular intervals or in response to specific events.
+
+**Raft Consensus Algorithm Security**
+* Cryptographic Integrity Checks: Apply asymmetric key cryptography hash functions TiKV instance nodes to data being replicated via the Raft algorithm to ensure data integrity.
+* Anomaly Detection in Raft Protocol: Develop anomaly detection systems that can identify unusual patterns in Raft elections or message flows, indicating a potential Byzantine attack. (Statistics Integration inside Placement Driver to search for anomalous behavior during Raft Consensus Algorithm)
+
+**Security in Multiversion Concurrency Control (MVCC)**
+* Timestamp Encryption and Validation: Encrypt timestamps and implement validation mechanisms to detect and prevent timestamp tampering.
+
+**RocksDB and TiKV's Storage Engine**
+* Implement Plugin-Based Encryption: Develop a plugin system for RocksDB to support Data-at-Rest encryption (DARE).
+* Vulnerability Scanning and Patching Process: Regularly scan for vulnerabilities in RocksDB and its dependencies, and establish a quick patching process
+(SBOMs, no detailed checkup system for open-source dependencies).
+
+ **Placement Driver Security**
+ * Distributed Trust and Consensus Mechanism: Implement a distributed trust and consensus mechanism for metadata changes in the Placement Driver.
+ * Backup and Recovery Plans: Establish robust backup and recovery plans for the metadata and transaction logs stored in the Placement Driver (Store two extra redundant copies of meta-data for recovery against data corruption – similar to the Raft Consensus Algorithm).
+
+**Timestamp Oracle Scalability and Security**
+* High-Availability Setup for Timestamp Oracle: Implement a high-availability setup for the Timestamp Oracle with automatic failover capabilities.
+* Rate Limiting and Queue Management: Introduce rate limiting and queue management to handle high demand without compromising security or performance.
+
+
+
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