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Projects MAY choose to omit specific interim versions from their public source repositories (e.g., ones that fix specific non-public security vulnerabilities, may never be publicly released, or include material that cannot be legally posted and are not in the final release).

This MAY be met in a variety of ways including a commit IDs (such as git commit id or mercurial changeset id) or a version number (including version numbers that use semantic versioning or date-based schemes like YYYYMMDD).

Projects should generally prefer whatever format is expected by their users, e.g., because it is the normal format used by their ecosystem. Many ecosystems prefer SemVer, and SemVer is generally preferred for application programmer interfaces (APIs) and software development kits (SDKs). CalVer tends to be used by projects that are large, have an unusually large number of independently-developed dependencies, have a constantly-changing scope, or are time-sensitive. It is SUGGESTED that those who use CalVer include a micro level value, because including a micro level supports simultaneously-maintained branches whenever that becomes necessary. Other version numbering formats may be used as version numbers, including git commit IDs or mercurial changeset IDs, as long as they uniquely identify versions. However, some alternatives (such as git commit IDs) can cause problems as release identifiers, because users may not be able to easily determine if they are up-to-date. The version ID format may be unimportant for identifying software releases if all recipients only run the latest version (e.g., it is the code for a single website or internet service that is constantly updated via continuous delivery).

The release notes MAY be implemented in a variety of ways. Many projects provide them in a file named "NEWS", "CHANGELOG", or "ChangeLog", optionally with extensions such as ".txt", ".md", or ".html". Historically the term "change log" meant a log of every change, but to meet these criteria what is needed is a human-readable summary. The release notes MAY instead be provided by version control system mechanisms such as the GitHub Releases workflow.

This criterion helps users determine if a given update will fix a vulnerability that is publicly known, to help users make an informed decision about updating. If users typically cannot practically update the software themselves on their computers, but must instead depend on one or more intermediaries to perform the update (as is often the case for a kernel and low-level software that is intertwined with a kernel), the project may choose "not applicable" (N/A) instead, since this additional information will not be helpful to those users. Similarly, a project may choose N/A if all recipients only run the latest version (e.g., it is the code for a single website or internet service that is constantly updated via continuous delivery). This criterion only applies to the project results, not its dependencies. Listing the vulnerabilities of all transitive dependencies of a project becomes unwieldy as dependencies increase and vary, and is unnecessary since tools that examine and track dependencies can do this in a more scalable way.

The response MAY be 'no' or a discussion about its merits. The goal is simply that there be some response to some requests, which indicates that the project is still alive. For purposes of this criterion, projects need not count fake requests (e.g., from spammers or automated systems). If a project is no longer making enhancements, please select "unmet" and include the URL that makes this situation clear to users. If a project tends to be overwhelmed by the number of enhancement requests, please select "unmet" and explain.

Projects hosted on GitHub SHOULD consider enabling privately reporting a security vulnerability. Projects on GitLab SHOULD consider using its ability for privately reporting a vulnerability. Projects MAY identify a mailing address on https://PROJECTSITE/security, often in the form security@example.org. This vulnerability reporting process MAY be the same as its bug reporting process. Vulnerability reports MAY always be public, but many projects have a private vulnerability reporting mechanism.

Examples include a private defect report submitted on the web using HTTPS (TLS) or an email encrypted using OpenPGP. If vulnerability reports are always public (so there are never private vulnerability reports), choose "not applicable" (N/A).

If there have been no vulnerabilities reported in the last 6 months, choose "not applicable" (N/A).

A build system determines what actions need to occur to rebuild the software (and in what order), and then performs those steps. For example, it can invoke a compiler to compile the source code. If an executable is created from source code, it must be possible to modify the project's source code and then generate an updated executable with those modifications. If the software produced by the project depends on external libraries, the build system does not need to build those external libraries. If there is no need to build anything to use the software after its source code is modified, select "not applicable" (N/A).

For example, Maven, Ant, cmake, the autotools, make, rake (Ruby), or devtools (R).

The project MAY use multiple automated test suites (e.g., one that runs quickly, vs. another that is more thorough but requires special equipment). There are many test frameworks and test support systems available, including Selenium (web browser automation), Junit (JVM, Java), RUnit (R), testthat (R).

For example, "make check", "mvn test", or "rake test" (Ruby).

As long as a policy is in place, even by word of mouth, that says developers should add tests to the automated test suite for major new functionality, select "Met."

Major functionality would typically be mentioned in the release notes. Perfection is not required, merely evidence that tests are typically being added in practice to the automated test suite when new major functionality is added to the software produced by the project.

However, even an informal rule is acceptable as long as the tests are being added in practice.

Examples of compiler warning flags include gcc/clang "-Wall". Examples of a "safe" language mode include JavaScript "use strict" and perl5's "use warnings". A separate "linter" tool is simply a tool that examines the source code to look for code quality errors or common simple mistakes. These are typically enabled within the source code or build instructions.

These are the warnings identified by the implementation of the warnings criterion. The project should fix warnings or mark them in the source code as false positives. Ideally there would be no warnings, but a project MAY accept some warnings (typically less than 1 warning per 100 lines or less than 10 warnings).

Some warnings cannot be effectively enabled on some projects. What is needed is evidence that the project is striving to enable warning flags where it can, so that errors are detected early.

This requires understanding the following design principles, including the 8 principles from Saltzer and Schroeder:

• economy of mechanism (keep the design as simple and small as practical, e.g., by adopting sweeping simplifications)
• fail-safe defaults (access decisions should deny by default, and projects' installation should be secure by default)
• complete mediation (every access that might be limited must be checked for authority and be non-bypassable)
• open design (security mechanisms should not depend on attacker ignorance of its design, but instead on more easily protected and changed information like keys and passwords)
• separation of privilege (ideally, access to important objects should depend on more than one condition, so that defeating one protection system won't enable complete access. E.G., multi-factor authentication, such as requiring both a password and a hardware token, is stronger than single-factor authentication)
• least privilege (processes should operate with the least privilege necessary)
• least common mechanism (the design should minimize the mechanisms common to more than one user and depended on by all users, e.g., directories for temporary files)
• psychological acceptability (the human interface must be designed for ease of use - designing for "least astonishment" can help)
• limited attack surface (the attack surface - the set of the different points where an attacker can try to enter or extract data - should be limited)
• input validation with allowlists (inputs should typically be checked to determine if they are valid before they are accepted; this validation should use allowlists (which only accept known-good values), not denylists (which attempt to list known-bad values)).

A "primary developer" in a project is anyone who is familiar with the project's code base, is comfortable making changes to it, and is acknowledged as such by most other participants in the project. A primary developer would typically make a number of contributions over the past year (via code, documentation, or answering questions). Developers would typically be considered primary developers if they initiated the project (and have not left the project more than three years ago), have the option of receiving information on a private vulnerability reporting channel (if there is one), can accept commits on behalf of the project, or perform final releases of the project software. If there is only one developer, that individual is the primary developer. Many books and courses are available to help you understand how to develop more secure software and discuss design. For example, the Secure Software Development Fundamentals course is a free set of three courses that explain how to develop more secure software (it's free if you audit it; for an extra fee you can earn a certificate to prove you learned the material).

Examples (depending on the type of software) include SQL injection, OS injection, classic buffer overflow, cross-site scripting, missing authentication, and missing authorization. See the CWE/SANS top 25 or OWASP Top 10 for commonly used lists. Many books and courses are available to help you understand how to develop more secure software and discuss common implementation errors that lead to vulnerabilities. For example, the Secure Software Development Fundamentals course is a free set of three courses that explain how to develop more secure software (it's free if you audit it; for an extra fee you can earn a certificate to prove you learned the material).

These cryptographic criteria do not always apply because some software has no need to directly use cryptographic capabilities.

See the Open Standards Requirement for Software by the Open Source Initiative.

These minimum bitlengths are: symmetric key 112, factoring modulus 2048, discrete logarithm key 224, discrete logarithmic group 2048, elliptic curve 224, and hash 224 (password hashing is not covered by this bitlength, more information on password hashing can be found in the crypto_password_storage criterion). See https://www.keylength.com for a comparison of keylength recommendations from various organizations. The software MAY allow smaller keylengths in some configurations (ideally it would not, since this allows downgrade attacks, but shorter keylengths are sometimes necessary for interoperability).

ECB mode is almost never appropriate because it reveals identical blocks within the ciphertext as demonstrated by the ECB penguin, and CTR mode is often inappropriate because it does not perform authentication and causes duplicates if the input state is repeated. In many cases it's best to choose a block cipher algorithm mode designed to combine secrecy and authentication, e.g., Galois/Counter Mode (GCM) and EAX. Projects MAY allow users to enable broken mechanisms (e.g., during configuration) where necessary for compatibility, but then users know they're doing it.

Concerns about CBC mode in SSH are discussed in CERT: SSH CBC vulnerability.

This criterion applies only when the software is enforcing authentication of users using passwords for external users (aka inbound authentication), such as server-side web applications. It does not apply in cases where the software stores passwords for authenticating into other systems (aka outbound authentication, e.g., the software implements a client for some other system), since at least parts of that software must have often access to the unhashed password.

A cryptographically secure random number generator may be a hardware random number generator, or it may be a cryptographically secure pseudo-random number generator (CSPRNG) using an algorithm such as Hash_DRBG, HMAC_DRBG, CTR_DRBG, Yarrow, or Fortuna. Examples of calls to secure random number generators include Java's java.security.SecureRandom and JavaScript's window.crypto.getRandomValues. Examples of calls to insecure random number generators include Java's java.util.Random and JavaScript's Math.random.

An even stronger mechanism is releasing the software with digitally signed packages, since that mitigates attacks on the distribution system, but this only works if the users can be confident that the public keys for signatures are correct and if the users will actually check the signature.

These hashes can be modified in transit.

The vulnerability must be patched and released by the project itself (patches may be developed elsewhere). A vulnerability becomes publicly known (for this purpose) once it has a CVE with publicly released non-paywalled information (reported, for example, in the National Vulnerability Database) or when the project has been informed and the information has been released to the public (possibly by the project). A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known. Note: this means that users might be left vulnerable to all attackers worldwide for up to 60 days. This criterion is often much easier to meet than what Google recommends in Rebooting responsible disclosure, because Google recommends that the 60-day period start when the project is notified even if the report is not public. Also note that this badge criterion, like other criteria, applies to the individual project. Some projects are part of larger umbrella organizations or larger projects, possibly in multiple layers, and many projects feed their results to other organizations and projects as part of a potentially-complex supply chain. An individual project often cannot control the rest, but an individual project can work to release a vulnerability patch in a timely way. Therefore, we focus solely on the individual project's response time. Once a patch is available from the individual project, others can determine how to deal with the patch (e.g., they can update to the newer version or they can apply just the patch as a cherry-picked solution).

A project MAY leak "sample" credentials for testing and unimportant databases, as long as they are not intended to limit public access.

A static code analysis tool examines the software code (as source code, intermediate code, or executable) without executing it with specific inputs. For purposes of this criterion, compiler warnings and "safe" language modes do not count as static code analysis tools (these typically avoid deep analysis because speed is vital). Some static analysis tools focus on detecting generic defects, others focus on finding specific kinds of defects (such as vulnerabilities), and some do a combination. Examples of such static code analysis tools include cppcheck (C, C++), clang static analyzer (C, C++), SpotBugs (Java), FindBugs (Java) (including FindSecurityBugs), PMD (Java), Brakeman (Ruby on Rails), lintr (R), goodpractice (R), Coverity Quality Analyzer, SonarQube, Codacy, and HP Enterprise Fortify Static Code Analyzer. Larger lists of tools can be found in places such as the Wikipedia list of tools for static code analysis, OWASP information on static code analysis, NIST list of source code security analyzers, and Wheeler's list of static analysis tools. If there are no FLOSS static analysis tools available for the implementation language(s) used, you may select 'N/A'.

Static analysis tools that are specifically designed to look for common vulnerabilities are more likely to find them. That said, using any static tools will typically help find some problems, so we are suggesting but not requiring this for the 'passing' level badge.

A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known. Note that criterion vulnerabilities_fixed_60_days requires that all such vulnerabilities be fixed within 60 days of being made public.

A dynamic analysis tool examines the software by executing it with specific inputs. For example, the project MAY use a fuzzing tool (e.g., American Fuzzy Lop) or a web application scanner (e.g., OWASP ZAP or w3af). In some cases the OSS-Fuzz project may be willing to apply fuzz testing to your project. For purposes of this criterion the dynamic analysis tool needs to vary the inputs in some way to look for various kinds of problems or be an automated test suite with at least 80% branch coverage. The Wikipedia page on dynamic analysis and the OWASP page on fuzzing identify some dynamic analysis tools. The analysis tool(s) MAY be focused on looking for security vulnerabilities, but this is not required.

Examples of mechanisms to detect memory safety problems include Address Sanitizer (ASAN) (available in GCC and LLVM), Memory Sanitizer, and valgrind. Other potentially-used tools include thread sanitizer and undefined behavior sanitizer. Widespread assertions would also work.

This criterion does not suggest enabling assertions during production; that is entirely up to the project and its users to decide. This criterion's focus is instead to improve fault detection during dynamic analysis before deployment. Enabling assertions in production use is completely different from enabling assertions during dynamic analysis (such as testing). In some cases enabling assertions in production use is extremely unwise (especially in high-integrity components). There are many arguments against enabling assertions in production, e.g., libraries should not crash callers, their presence may cause rejection by app stores, and/or activating an assertion in production may expose private data such as private keys. Beware that in many Linux distributions NDEBUG is not defined, so C/C++ assert() will by default be enabled for production in those environments. It may be important to use a different assertion mechanism or defining NDEBUG for production in those environments.

If you are not running dynamic code analysis and thus have not found any vulnerabilities in this way, choose "not applicable" (N/A). A vulnerability is considered medium or higher severity if its Common Vulnerability Scoring System (CVSS) base qualitative score is medium or higher. In CVSS versions 2.0 through 3.1, this is equivalent to a CVSS score of 4.0 or higher. Projects may use the CVSS score as published in a widely-used vulnerability database (such as the National Vulnerability Database) using the most-recent version of CVSS reported in that database. Projects may instead calculate the severity themselves using the latest version of CVSS at the time of the vulnerability disclosure, if the calculation inputs are publicly revealed once the vulnerability is publicly known.