THREAT-MODEL-FLASK-o1-preview.md

APPLICATION THREAT MODEL

ASSETS

1. User Data: Information submitted by users via web forms, including usernames, passwords, and personal details.
2. Session Data: Session cookies and tokens used to maintain user sessions and authentication state.
3. Application Code: The source code of the Flask application, including Python scripts, HTML templates, and static files.
4. Configuration Files: Files containing sensitive settings such as secret keys, database connection strings, and API keys.
5. Database: Stores persistent data, such as user accounts, posts, and other application-specific information.
6. Authentication Credentials: Usernames and passwords used for user authentication within the application.
7. Templates: Jinja2 templates used to render dynamic HTML pages.
8. Logs: Application logs that may contain sensitive information or error messages.
9. API Endpoints: URLs exposed by the application to allow client interactions via HTTP methods.
10. Static Files: Assets such as JavaScript, CSS, images, and other resources served to the client.
11. Test Code and Data: Unit tests, integration tests, and test data that may contain sensitive information or example credentials.
12. Documentation Files: ReStructuredText and other documentation files that may contain code examples, configuration snippets, or sensitive information.

TRUST BOUNDARIES

1. User Browser to Flask Application Server: The boundary between the untrusted client-side environment (user's browser) and the trusted server-side application.
2. Flask Application Server to Database: The boundary between the application logic and the backend database storing sensitive data.
3. Flask Application Server to Third-Party Extensions: The use of external Flask extensions and modules that may not be fully trusted.
4. Flask Application Server to External Services: Interactions with external APIs or services outside the application's control.
5. Test Environment to Production Environment: The boundary between test code/data and the production application code.
6. Documentation Files to Public Repository: The boundary between internal documentation and what is published publicly.

DATA FLOWS

1. User Inputs (HTTP Requests): Data sent from the user's browser to the Flask application server through forms or API requests. (Crosses Trust Boundary 1)
2. Server Responses (HTTP Responses): Data sent from the Flask application server back to the user's browser, including HTML pages and JSON data. (Crosses Trust Boundary 1)
3. Session Tokens: Session data exchanged between the client and server to maintain user authentication state. (Crosses Trust Boundary 1)
4. Database Queries: Data flow from the Flask application server to the database when performing CRUD operations. (Crosses Trust Boundary 2)
5. Database Responses: Data retrieved from the database and sent back to the Flask application server. (Crosses Trust Boundary 2)
6. Interactions with Third-Party Extensions: Data handled by external Flask extensions within the application.
7. External API Calls: Data sent to and received from external services or APIs. (Crosses Trust Boundary 4)
8. Testing Code Execution: Data flow from test code to application code during the testing phase. (Crosses Trust Boundary 5)
9. Documentation Publication: Data flow from internal documentation files to public repositories or documentation hosting services. (Crosses Trust Boundary 6)

APPLICATION THREATS

THREAT ID	COMPONENT NAME	THREAT NAME	STRIDE CATEGORY	WHY APPLICABLE	HOW MITIGATED	MITIGATION	LIKELIHOOD EXPLANATION	IMPACT EXPLANATION	RISK SEVERITY
0001	User Input Handling	SQL Injection via User Input Forms	Tampering	The application accepts user inputs that could be used to inject malicious SQL queries if not properly sanitized or parameterized.	Not fully mitigated if user inputs are directly used in SQL queries without proper handling.	Use parameterized queries or ORM methods to safely handle user inputs; validate and sanitize all user inputs before using them in database operations.	High likelihood if input is not properly validated; SQL injection is a common attack vector for web applications.	High impact as attackers can manipulate or access sensitive data in the database, leading to data breach or loss.	Critical
0002	Template Rendering	Cross-Site Scripting (XSS) through Unsanitized Template Variables	Information Disclosure	User-supplied data may be rendered in templates without proper escaping, allowing attackers to inject malicious scripts into web pages viewed by others.	Flask's Jinja2 templates auto-escape variables by default; however, developers may disable auto-escaping or use the `	safe` filter improperly, which reintroduces the risk.	Ensure that auto-escaping is enabled in Jinja2 templates; avoid using the `	safe` filter on untrusted user inputs; validate and sanitize data before rendering.	Medium likelihood if developers disable auto-escaping or fail to handle inputs securely.
0003	Session Management	Session Hijacking via Predictable Session Tokens	Spoofing	If session tokens are predictable or transmitted over insecure channels, attackers can hijack user sessions by intercepting or guessing the tokens.	Flask uses secure cookies for session management, but if configured improperly (e.g., missing SESSION_COOKIE_SECURE), the risk remains.	Configure the application to use secure session cookies by setting SESSION_COOKIE_SECURE=True and SESSION_COOKIE_HTTPONLY=True; ensure all communications use HTTPS to protect tokens in transit.	Medium likelihood if secure practices are not followed; attackers can sniff tokens over unsecured connections or predict them if they are weak.	High impact as attackers can gain unauthorized access to user accounts, leading to data breaches and unauthorized actions within the application.	High
0004	User Authentication	Brute Force Attack on Login	Denial of Service	Attackers may attempt to gain unauthorized access by repeatedly guessing usernames and passwords through automated scripts.	Not mitigated if there are no mechanisms in place to detect and prevent multiple failed login attempts.	Implement account lockout policies after several failed attempts; use CAPTCHAs to prevent automated submissions; monitor and rate-limit login attempts from suspicious sources.	High likelihood as automated tools make it easy to perform brute force attacks if no protections are in place.	Medium impact due to potential compromise of user accounts and increased server load, which can degrade performance for legitimate users.	High
0005	CSRF Protection	Cross-Site Request Forgery (CSRF) Attacks	Tampering	Without CSRF protection, attackers can trick authenticated users into submitting malicious requests unknowingly.	Flask does not include CSRF protection by default; developers must implement it using extensions like Flask-WTF or custom middleware.	Use CSRF tokens in all forms and validate them on the server side; implement CSRF protection using Flask-WTF or similar libraries; ensure tokens are unique per session and request.	High likelihood if CSRF protection is not implemented; attackers can easily craft malicious links or forms to exploit users.	High impact as attackers can perform unauthorized actions on behalf of users, such as changing account details or making transactions.	High
0006	Error Handling	Information Disclosure via Detailed Error Messages	Information Disclosure	Detailed error messages may reveal sensitive information about the application's code structure, configuration, or database schema to attackers.	By default, Flask shows detailed error messages when DEBUG mode is enabled; in production, if DEBUG is not set to False, this risk persists.	Ensure that DEBUG=False in production environments; configure custom error handlers to display generic error messages; avoid showing stack traces or sensitive data in error responses.	Low likelihood if application is properly configured for production; higher if developers forget to disable debug mode.	Medium impact as disclosed information can aid attackers in finding other vulnerabilities or understanding the application's internals.	Medium
0007	Data Storage	Sensitive Data Stored in Plaintext (e.g., Passwords)	Information Disclosure	If sensitive data like user passwords are stored without hashing, they can be compromised if the database is breached.	Not mitigated if the application stores passwords or other sensitive data in plaintext without encryption or hashing.	Use strong, one-way hashing algorithms like bcrypt to store passwords; avoid storing sensitive data unless necessary; implement encryption for sensitive data at rest.	Medium likelihood if secure storage practices are neglected; databases are common targets for attackers seeking valuable data.	High impact as compromised data can lead to further attacks, identity theft, and loss of user trust in the application.	High
0008	Input Validation	Denial of Service via Large Payloads	Denial of Service	Attackers may send excessively large requests or upload files to consume server resources, leading to service degradation or crash.	Not mitigated if the application does not enforce limits on request size or the number of request parameters.	Set MAX_CONTENT_LENGTH, MAX_FORM_MEMORY_SIZE, and MAX_FORM_PARTS in the Flask configuration to limit input sizes; validate input data sizes on the server side before processing.	Medium likelihood as attacks exploiting resource consumption are common and easy to perform without proper safeguards.	High impact as the application may become unresponsive or crash, leading to downtime and denial of service to legitimate users.	High
0009	Logging	Sensitive Data Exposure in Logs	Information Disclosure	Application logs might inadvertently record sensitive information like passwords, session tokens, or personal data.	Not mitigated if logging is configured to include request payloads or sensitive variables without filtering.	Review and configure logging to exclude sensitive data; implement log sanitization; follow best practices for secure logging and monitor access to log files.	Medium likelihood if logging practices do not consider security; developers may overlook the sensitivity of data being logged.	Medium impact as exposed logs can be accessed by unauthorized parties, leading to data breaches and compliance violations.	Medium
0010	Third-Party Modules	Execution of Malicious Code via Untrusted Extensions	Elevation of Privilege	Using outdated or untrusted third-party modules and extensions may introduce vulnerabilities or malicious code into the application.	Not mitigated if dependencies are not regularly reviewed, updated, or sourced from reputable providers.	Use third-party extensions and modules from trusted sources; keep all dependencies updated to the latest secure versions; employ tools to scan for known vulnerabilities in dependencies.	Medium likelihood due to the prevalence of supply-chain attacks targeting dependencies; risk increases with lack of vigilance.	High impact as malicious code can compromise the entire application, leading to data breaches, unauthorized access, or complete system compromise.	High
0011	Test Code	Exposure of Sensitive Test Data or Credentials in Production Environment	Information Disclosure	Test code and data, such as 'tests/type_check/*.py', may include hardcoded credentials, secret keys, or example configurations that can be inadvertently included in the production deployment.	Not fully mitigated if test code and data are not properly separated from production code during build and deployment; files like 'tests/type_check/typing_app_decorators.py' may be included unintentionally.	Ensure that test code and data are excluded from production builds; update build scripts to ignore 'tests/' directory; review codebase to remove any hardcoded sensitive information; implement code reviews focusing on test code inclusion.	Medium likelihood if test code is not properly managed and excluded from production; developers may forget to exclude test files.	High impact as leaked credentials or sensitive data can lead to unauthorized access and compromise of the application.	High
0012	Application Routes	Accidental Exposure of Test or Debug Endpoints in Production	Information Disclosure	Test code may define routes or endpoints used for testing purposes that should not be accessible in production.	Not mitigated if test routes are not disabled or removed before deployment.	Implement environment-specific routing to exclude test and debug endpoints in production; use configuration flags to enable test routes only in development environments.	Medium likelihood if test code is not properly isolated; developers may inadvertently include test endpoints.	Medium impact as exposed test endpoints may reveal application internals or allow unintended actions.	Medium
0013	Application Code	Injection of Malicious Code via Compromised Test Scripts	Tampering	Test scripts may be altered by an attacker to introduce malicious code, which could be executed when tests are run.	Not mitigated if access to test code is not properly restricted.	Restrict access to test code repositories; implement code reviews and integrity checks; use version control systems with access control.	Low likelihood if access controls are in place; higher if test code is publicly accessible.	High impact as malicious code could be executed, leading to compromise of the application or infrastructure.	Medium
0014	Documentation Files	Disclosure of Sensitive Information via Documentation Files	Information Disclosure	Documentation files may inadvertently contain sensitive information such as secret keys, passwords, or internal IP addresses, which could be exposed if the files are published publicly.	Not mitigated if documentation files are not reviewed for sensitive information before publication.	Implement a review process to ensure documentation does not contain sensitive information; use automated tools to scan for secrets in documentation files before publishing.	Medium likelihood if documentation practices are lax; developers may include sensitive information in examples or configuration snippets inadvertently.	High impact as disclosed secrets can lead to unauthorized access, data breaches, or compromise of the application and infrastructure.	High

DEPLOYMENT THREAT MODEL

ASSETS

1. Production WSGI Server: The server (e.g., Gunicorn, uWSGI, Waitress) used to host the Flask application in production.
2. Reverse Proxy Server: A server like Nginx or Apache httpd configured to route external requests to the WSGI server.
3. TLS/SSL Certificates: Private keys and certificates used for HTTPS connections.
4. Deployment Configuration Files: Configuration files for WSGI servers, reverse proxies, and the application.
5. Application Code: The source code of the Flask application deployed in production.
6. Host Operating System: The operating system on which the application and supporting services are running.
7. Network Infrastructure: The network environment in which the application operates, including firewalls, routers, and switches.
8. Secrets and Credentials: Environment variables and configuration files containing sensitive information like database passwords, API keys, and other credentials used during deployment.
9. Logs: Logs generated by the application and servers, which may contain sensitive information.
10. External Services: Third-party services and APIs that the application interacts with during deployment and runtime.
11. Package Dependencies: Third-party libraries and packages installed during deployment from package repositories.

TRUST BOUNDARIES

1. Internet to Reverse Proxy Server: The boundary between untrusted external users and the reverse proxy server.
2. Reverse Proxy Server to WSGI Server: The internal boundary where traffic is forwarded from the reverse proxy to the application server.
3. WSGI Server to Flask Application: The boundary between the WSGI server process and the application code.
4. WSGI Server to Database: The boundary between the application server and the database server.
5. Deployment Environment to Production Environment: The boundary between systems used for deployment and the production environment.
6. Configuration Management System to Deployment Environment: The boundary where configuration files and secrets are supplied to the deployment environment.
7. Host Operating System to Application/Services: The boundary between the OS and the application processes.
8. Application Server to External Services: The boundary between the application and any external services or APIs it depends on.
9. Package Repository to Deployment Environment: The boundary crossed when fetching dependencies from external package repositories.

DEPLOYMENT THREATS

THREAT ID	COMPONENT NAME	THREAT NAME	WHY APPLICABLE	HOW MITIGATED	MITIGATION	LIKELIHOOD EXPLANATION	IMPACT EXPLANATION	RISK SEVERITY
2001	Reverse Proxy Server	Misconfigured Reverse Proxy Exposes Internal Services	If the reverse proxy is not configured correctly, it may inadvertently expose internal services or configurations to the Internet.	Not fully mitigated if deployment relies on default configurations or manual setups without security review.	Review and harden the reverse proxy configuration; restrict access to internal services using allow/deny rules; ensure only intended ports and services are exposed.	Medium likelihood due to configuration errors or oversight in complex setups.	High impact as exposure of internal services could lead to unauthorized access, data breaches, or further exploitation.	High
2002	WSGI Server	Use of Development Server (Werkzeug) in Production Environment	The application may inadvertently be run using the development server, which is not designed for production use and lacks security hardening.	Not mitigated if there are no checks to prevent the use of the development server in production.	Ensure that production deployments use a production-grade WSGI server (e.g., Gunicorn, uWSGI); include checks or documentation to prevent misuse.	Low to medium likelihood if deployment processes are not standardized or enforced.	High impact as the development server has known security weaknesses and performance issues.	High
2003	TLS/SSL Certificates	Compromise of TLS/SSL Private Keys	If the private keys for TLS/SSL certificates are compromised, attackers can perform man-in-the-middle attacks or decrypt secure traffic.	Not fully mitigated if private keys are not stored securely or not rotated regularly.	Implement strong security controls for storing and accessing private keys; use hardware security modules (HSMs) or key vaults; enforce strict access controls.	Medium likelihood due to potential for insider threats or external compromises.	Critical impact as compromise of TLS keys undermines all secure communications, leading to potential data breaches and loss of trust.	Critical
2004	Deployment Configuration Files	Exposure of Sensitive Configuration Files through Misconfigured Servers	If the web server is misconfigured, it may serve sensitive configuration files (e.g., app config, environment files) which can include secrets.	Not fully mitigated if the server allows directory listing or doesn't prevent access to configuration files.	Configure web servers to prevent access to sensitive files; ensure that only necessary files are served; validate server configurations regularly.	Medium likelihood if configurations are not properly reviewed.	High impact as exposure of configuration files can leak secrets, credentials, and internal architecture details.	High
2005	Host Operating System	Unpatched OS Vulnerabilities Lead to Compromise	Running the application on an OS that is not regularly updated can expose it to known vulnerabilities that attackers can exploit.	Partially mitigated if the system uses automatic updates but may not be fully up-to-date.	Implement a process for regular OS updates and patches; use configuration management tools to enforce consistency and compliance.	Medium likelihood if updates are not automated or are overlooked.	High impact as attackers can exploit known vulnerabilities to gain access or escalate privileges, compromising the entire system.	High
2006	Application Server to External Services	Insecure Communication with External Services	If the application communicates with external services over unencrypted channels, data could be intercepted or tampered with by attackers.	Not mitigated if the application does not use HTTPS or secure protocols for external communications.	Enforce the use of TLS/SSL for all external communication; validate certificates; implement secure coding practices and libraries for network communication.	Medium likelihood if developers are not vigilant in enforcing secure communications.	High impact as sensitive data could be compromised, leading to data breaches and loss of integrity and confidentiality.	High
2007	Package Dependencies	Inclusion of Malicious or Vulnerable Dependencies During Deployment	Dependencies specified in deployment may be compromised via typosquatting or outdated versions may have known vulnerabilities; some dependencies may lack strict version pins.	Not fully mitigated if dependencies are not regularly audited or pinned to specific secure versions; if version ranges are broad, updates may introduce vulnerabilities.	Regularly audit dependencies; pin to known secure versions; use tools to check for known vulnerabilities; consider dependency locking or hash-based pinning.	Medium to high likelihood due to the prevalence of supply chain attacks targeting dependencies.	High impact as compromised dependencies could execute malicious code within the application, leading to data breaches or system compromise.	High

BUILD THREAT MODEL

ASSETS

1. Source Code Repository: The GitHub repository containing the Flask application's source code.
2. CI/CD Pipelines: GitHub Actions workflows and scripts used for building, testing, and deploying the application.
3. Secrets and Credentials: API keys, tokens, and other sensitive credentials used within CI/CD pipelines.
4. Build Artifacts: Distributions, Docker images, or other artifacts produced during the build process.
5. Package Publishing: Access and credentials for publishing packages to package repositories like PyPI.
6. Test Scripts and Automation: Test scripts and automated test suites used in the build and continuous integration process.
7. Dependency Configuration Files: Files specifying project dependencies, such as 'requirements/*.txt' and 'pyproject.toml'.

TRUST BOUNDARIES

1. GitHub Actions Runner Environment: The execution environment provided by GitHub where workflows run.
2. Third-Party Actions and Dependencies: External actions and libraries used within workflows and the application.
3. Public vs. Private Repositories: Boundary between publicly accessible code and private, internal configurations and secrets.
4. CI/CD to Package Registry: The interface between the build pipeline and external package registries like PyPI.
5. Test Environment to Build Environment: The boundary between test scripts and the build environment where they are executed.
6. Dependency Sources: The boundary between trusted dependency sources (e.g., PyPI) and untrusted sources (e.g., external git repositories).

BUILD THREATS

THREAT ID	COMPONENT NAME	THREAT NAME	WHY APPLICABLE	HOW MITIGATED	MITIGATION	LIKELIHOOD EXPLANATION	IMPACT EXPLANATION	RISK SEVERITY
1001	CI/CD Pipelines	Compromise of CI/CD Pipeline via Malicious Pull Requests	Open-source projects may receive pull requests that attempt to modify workflows or introduce malicious code into the build.	Not fully mitigated if workflows automatically run on all pull requests without proper permissions or reviews.	Require approval for workflow changes; use code owners and branch protection rules; limit permissions of workflows; use pull_request_target judiciously.	Medium likelihood due to potential for attackers to target CI/CD pipelines in popular repositories.	High impact as compromised pipelines can lead to execution of malicious code, exposure of secrets, or distribution of compromised builds.	High
1002	Secrets Management	Exposure of Secrets in CI/CD Logs	Secrets used in workflows might be accidentally printed to logs, which can then be accessed by unauthorized individuals.	GitHub Actions masks secrets by default, but improper logging statements can still expose them.	Avoid printing secrets in logs; use environment variables securely; review workflows to ensure secrets are not echoed or logged; enable secret scanning tools to detect leaks.	Medium likelihood if developers include verbose logging without considering sensitive data; mistakes can happen.	High impact as exposed secrets can compromise accounts, services, or the entire application infrastructure.	High
1003	Third-Party Actions	Use of Malicious or Vulnerable Third-Party GitHub Actions	Workflows may include actions maintained by third parties, which might contain vulnerabilities or malicious code.	Not mitigated if actions are used without verification or are not pinned to specific versions.	Use actions from verified creators; pin actions to specific commit SHAs or release tags; review action code if necessary; limit actions' permissions.	Medium likelihood given the increasing number of supply-chain attacks; attackers may target popular actions.	High impact as malicious actions can execute code within the CI environment, leading to compromise of the build process or exposure of secrets.	High
1004	Dependency Management	Inclusion of Malicious or Vulnerable Dependencies during Build	Dependencies specified in 'requirements/*.txt' may be compromised via typosquatting or trusted packages may have vulnerabilities; some dependencies lack strict version pins or use broad version ranges.	Not mitigated if dependencies are not regularly audited or if version pins are not used to control updates; 'requirements/tests-dev.txt' includes unpinned dependencies from GitHub URLs.	Regularly audit dependencies using tools like pip-audit; pin dependencies to known secure versions; use hashes in requirements.txt; avoid using broad version ranges; monitor for CVEs and update dependencies promptly.	High likelihood due to potential for dependency confusion or inclusion of vulnerable packages; risk increases with unpinned or loosely pinned dependencies.	High impact as vulnerable or malicious dependencies can lead to code execution within the application or disclosure of sensitive data.	High
1005	Build Artifacts	Tampering with Build Artifacts before Publishing	Build artifacts may be tampered with if stored in insecure locations before being published to package registries.	Not mitigated if artifacts are not securely stored or checksummed before publishing.	Store artifacts in secure, access-controlled locations; use checksum verification; implement artifact signing; ensure CI/CD pipelines are secure.	Low likelihood if best practices for artifact security are followed; higher if artifacts are stored insecurely.	High impact as tampered artifacts can introduce vulnerabilities or backdoors into distributed packages, affecting all users of the package.	High
1006	Publishing Credentials	Unauthorized Access to Package Publishing Credentials (e.g., PyPI API Tokens)	API tokens used for publishing can be targeted by attackers to publish malicious versions of the package.	Not mitigated if credentials are not securely stored or if access controls are weak.	Store publishing credentials as encrypted secrets; restrict access to necessary scopes; use MFA for accounts; rotate tokens regularly; limit token lifespan.	Medium likelihood if secrets management is lax; attackers actively seek out exposed credentials in repositories.	High impact as compromised publishing credentials can allow attackers to distribute malicious packages under the trusted package name.	High
1007	Code Integrity	Lack of Code Signing for Published Packages	Without code signing, there is no verification that the packages downloaded by users are the ones actually published.	Not mitigated if no code signing mechanism is in place for the distributed packages.	Implement code signing for packages using tools like TUF (The Update Framework) or PEP 458/480; encourage users to verify signatures before installation.	Medium likelihood as code signing is not yet widely adopted; attackers may intercept or replace packages during distribution.	Medium impact as users could install tampered packages, leading to widespread security incidents and loss of trust in the package maintainer.	Medium
1008	GitHub Actions Runner	Compromise of GitHub Actions Runner Environment	Attackers may compromise the runner environment to intercept secrets or influence the build process.	Not fully mitigated if self-hosted runners are used without proper security measures; GitHub-hosted runners are generally secure.	Use GitHub-hosted runners when possible; if self-hosted, ensure runners are securely configured and patched; limit exposure and access to runner machines.	Low likelihood for GitHub-hosted runners; higher for self-hosted runners which may not be as securely managed.	High impact as compromised runners can lead to full control over the build environment, exposure of secrets, and compromised build outputs.	High
1009	Test Scripts and Automation	Execution of Malicious Test Scripts during Build Process	If test scripts contain malicious code or are altered by an attacker, executing them during the build can compromise the build environment.	Not fully mitigated if test scripts are not reviewed or access-controlled.	Secure test script repositories; enforce code reviews; restrict who can modify test scripts; use automated security scanning on test code.	Low likelihood if proper controls are in place; risk increases if test scripts are not secured.	High impact as malicious scripts could lead to compromise of the build environment and insertion of vulnerabilities into the application.	High
1010	Dependency Management	Insecure Download of Dependencies from Unverified Sources	Dependencies are specified in 'requirements/tests-dev.txt' using direct URLs to GitHub repositories, which may be compromised or altered by attackers.	Not mitigated if dependencies are downloaded from external sources without verification; using URLs to 'main' branches can introduce risks of code changes.	Pin dependencies to specific commit SHAs or tags; verify integrity of dependencies using checksums; avoid using external sources unless necessary; use trusted package registries.	Medium likelihood due to reliance on external repositories that could be compromised or updated with malicious code; risk increases without verification steps.	High impact as malicious dependencies can execute code during the build or runtime, leading to compromise of the application or exposure of sensitive data.	High

QUESTIONS & ASSUMPTIONS

• Assumptions:

  • The application is deployed using a production-grade WSGI server (e.g., Gunicorn, uWSGI, Waitress) as per the deployment documentation.
  • The reverse proxy (e.g., Nginx, Apache httpd) is properly configured to forward requests to the WSGI server and to handle TLS termination.
  • TLS/SSL certificates are managed securely and are valid.
  • Deployment configurations are managed appropriately and secured against unauthorized access.
  • Regular updates and patches are applied to the host operating system and all server software.
  • Dependencies are regularly audited and updated to address known vulnerabilities.
  • Secure communication protocols are enforced for all external services.
  • Access to deployment infrastructure and secrets is restricted to authorized personnel.

• Questions:

  • How are TLS/SSL certificates stored and managed? Are there procedures for rotation and revocation?
  • What processes are in place to ensure that production deployments use the correct WSGI server and configurations, and not the development server?
  • Are there regular audits of reverse proxy configurations to prevent accidental exposure of internal services?
  • How are deployment configuration files protected from unauthorized access or exposure?
  • Is there a process for regular system updates and patches for the host OS and server software?
  • How are package dependencies managed during deployment? Are they pinned and audited for vulnerabilities?
  • Are external communications validated to ensure they use secure protocols and valid certificates?
  • What measures are in place to prevent the inclusion of malicious dependencies during deployment?
  • Is there monitoring and alerting in place to detect potential compromises or misconfigurations in the deployment environment?

---