Add new plugin Recaptcha3Token that sends the reCaptcha v3 token to the back-end when the form is valid

All validators can be used independently. Inspried by functional programming paradigm, all built in validators are just functions.

FormValidation.validators.creditCard().validate({

FormValidation.formValidation(formElement

that a better and cleaner approach would be to use computed properties and a validation library that is decoupled for the UI (like hapi/joi).

These all come from the HTML Standard.

setCustomValidity

Note that we added HTML validation with specifying the types of the field (email and password). This allows the browser to validate the input.

We must always return at least some validation rule. So first off if value !== undefined then we'll return our previous validation schema. If it is undefined then we'll use the yup.mixed().notRequired() which will just inform yup that nothing is required at the optionalObject level. optionalObject: yup.lazy(value => { if (value !== undefined) { return yup.object().shape({ otherData: yup.string().required(), }); } return yup.mixed().notRequired(); }),

Mark the schema as required. All field values apart from undefined and null meet this requirement.

The same as the mixed() schema required, except that empty strings are also considered 'missing' values.

Form validation is hard. That's why there are so many different form handling libraries for the popular web frameworks. It's usually not something that is built-it, because everyone has a different need and there is no one-fit-all solution.

Triggers error messages to render after a field is touched, and blurred (focused out of), this is useful for text fields which might start out erronous but end up valid in the end (i.e. email, or zipcode). In these cases you don't want to rush to show the user a validation error message when they haven't had a chance to finish their entry.

Triggers error messages to show up as soon as a value of a field changes. Useful for when the user needs instant feedback from the form validation (i.e. password creation rules, non-text based inputs like select, or switches etc.)

Constraints

The bindings are two-way because any HTML5 contraint validation errors will be added to the Final Form state, and any field-level validation errors from Final Form will be set into the HTML5 validity.customError state.

So when we ask users to answer questions that deal with the future, we have to keep in mind the context in which they’re answering. They can tell us about a feature they think will make their lives better, but user val-idation will always be necessary to make sure that past user’s beliefs about future user are accurate.

It's worth pointing out that filenames can contain a newline character on many *nix systems. You're unlikely to ever run into this in the wild, but if you're running shell commands on untrusted input this could be a concern

To verify that your structured data is correct, many platforms provide validation tools. In this tutorial, we'll validate our structured data with the Google Structured Data Validation Tool.

Currently, if we have an invalid mouse association that was previously saved at some point in the past (eg. with mouse.save! validate: false)

There's not a way to do this. What you could do instead is use Cloud Functions HTTP triggers as an API for writing data. It could check the conditions you want, then return a response that indicates what's wrong with the data the client is trying to write. I understand this is far from ideal, but it might be the best option you have right now

(Thus, for these curves, the cofactor is always h = 1.)

As mentioned in StateMachines::Machine#state, you can define behaviors, like validations, that only execute for certain states. One important caveat here is that, due to a constraint in ActiveRecord's validation framework, custom validators will not work as expected when defined to run in multiple states.

1- Validation: you “validate”, ie deem valid or invalid, data at input time. For instance if asked for a zipcode user enters “zzz43”, that’s invalid. At this point, you can reject or… sanitize. 2- sanitization: you make data “sane” before storing it. For instance if you want a zipcode, you can remove any character that’s not [0-9] 3- escaping: at output time, you ensure data printed will never corrupt display and/or be used in an evil way (escaping HTML etc…)

This style of validation most closely follows WordPress’ whitelist philosophy: only allow the user to input what you’re expecting.

What Is Input Validation and Sanitization? Validation checks if the input meets a set of criteria (such as a string contains no standalone single quotation marks). Sanitization modifies the input to ensure that it is valid (such as doubling single quotes).

Having visibility to the prevalence means, for example, you might outright block every password that's appeared 100 times or more and force the user to choose another one (there are 1,858,690 of those in the data set), strongly recommend they choose a different password where it's appeared between 20 and 99 times (there's a further 9,985,150 of those), and merely flag the record if it's in the source data less than 20 times.

Validators, like all attribute extensions, are only called by normal userland code; they are not issued when the ORM is populating the object

validates works only during append operation. Not during assignment

Designers using these curves should be aware that for each public key, there are several publicly computable public keys that are equivalent to it, i.e., they produce the same shared secrets. Thus using a public key as an identifier and knowledge of a shared secret as proof of ownership (without including the public keys in the key derivation) might lead to subtle vulnerabilities.

Protocol designers using Diffie-Hellman over the curves defined in this document must not assume "contributory behaviour". Specially, contributory behaviour means that both parties' private keys contribute to the resulting shared key. Since curve25519 and curve448 have cofactors of 8 and 4 (respectively), an input point of small order will eliminate any contribution from the other party's private key. This situation can be detected by checking for the all- zero output, which implementations MAY do, as specified in Section 6. However, a large number of existing implementations do not do this.

The check for the all-zero value results from the fact that the X25519 function produces that value if it operates on an input corresponding to a point with small order, where the order divides the cofactor of the curve (see Section 7).

Both MAY check, without leaking extra information about the value of K, whether K is the all-zero value and abort if so (see below).

n

an ECC key-establishment scheme requires the use of public keys that are affine elliptic-curve points chosen from a specific cyclic subgroup with prime order n

5.6.2.3.3ECC Full Public-Key Validation Routine

The recipient performs a successful full public-key validation of the received public key (see Sections 5.6.2.3.1for FFCdomain parameters andSection5.6.2.3.3for ECCdomain parameters).

Assurance of public-key validity –assurance that the public key of the other party (i.e., the claimed owner of the public key) has the (unique) correct representation for a non-identity element of the correct cryptographic subgroup, as determined by the

outside the subgroup

5.6.2.3.2ECC Full Public-Key Validation Routine

The recipient performs a successful full public-key validation of the received public key (see Sections 5.6.2.3.1 and 5.6.2.3.2).

Assurance of public-key validity – assurance that the public key of the other party (i.e., the claimed owner of the public key) has the (unique) correct representation for a non-identity element of the correct cryptographic subgroup, as determined by the domain parameters (see Sections 5.6.2.2.1 and 5.6.2.2.2). This assurance is required for both static and ephemeral public keys.

Misusing public keys as secrets: It might be tempting to use a pattern with a pre-message public key and assume that a successful handshake implies the other party's knowledge of the public key. Unfortunately, this is not the case, since setting public keys to invalid values might cause predictable DH output. For example, a Noise_NK_25519 initiator might send an invalid ephemeral public key to cause a known DH output of all zeros, despite not knowing the responder's static public key. If the parties want to authenticate with a shared secret, it should be used as a PSK.

Channel binding: Depending on the DH functions, it might be possible for a malicious party to engage in multiple sessions that derive the same shared secret key by setting public keys to invalid values that cause predictable DH output (as in the previous bullet). It might also be possible to set public keys to equivalent values that cause the same DH output for different inputs. This is why a higher-level protocol should use the handshake hash (h) for a unique channel binding, instead of ck, as explained in Section 11.2.

The public_key either encodes some value which is a generator in a large prime-order group (which value may have multiple equivalent encodings), or is an invalid value. Implementations must handle invalid public keys either by returning some output which is purely a function of the public key and does not depend on the private key, or by signaling an error to the caller. The DH function may define more specific rules for handling invalid values.

WireGuard excludes zero Diffie-Hellman shared secrets to avoid points of small order, while Noiserecommends not to perform this check

This check strikes a delicate balance: It checks Y sufficiently to prevent forgery of a (Y, Y^x) pair without knowledge of X, but the rejected values for X are unlikely to be hit by an attacker flipping ciphertext bits in the least-significant portion of X. Stricter checking could easily *WEAKEN* security, e.g. the NIST-mandated subgroup check would provide an oracle on whether a tampered X was square or nonsquare.

X25519 is very close to this ideal, with the exception that public keys have easily-computed equivalent values. (Preventing equivalent values would require a different and more costly check. Instead, protocols should "bind" the exact public keys by MAC'ing them or hashing them into the session key.)

Curve25519 key generation uses scalar multiplication with a private key "clamped" so that it will always produce a valid public key, regardless of RNG behavior.

* Valid points have equivalent "invalid" representations, due to the cofactor, masking of the high bit, and (in a few cases) unreduced coordinates.

With all the talk of "validation", the reader of JP's essay is likely to think this check is equivalent to "full validation" (e.g. [SP80056A]), where only valid public keys are accepted (i.e. public keys which uniquely encode a generator of the correct subgroup).

(1) The proposed check has the goal of blacklisting a few input values. It's nowhere near full validation, does not match existing standards for ECDH input validation, and is not even applied to the input.

If Alice generates all-zero prekeys and identity key, and pushes them to the Signal’s servers, then all the peers who initiate a new session with Alice will encrypt their first message with the same key, derived from all-zero shared secrets—essentially, the first message will be in the clear for an eavesdropper.

arguing that a zero check “adds complexity (const-time code, error-handling, and implementation variance), and is not needed in good protocols.”

Responders don't use valid? to check for errors in models to figure out if the request was successful or not, and relies on your controllers to call save or create to trigger the validations.

Arguably, the rails-team's choice of raising ArgumentError instead of validation error is correct in the sense that we have full control over what options a user can select from a radio buttons group, or can select over a select field, so if a programmer happens to add a new radio button that has a typo for its value, then it is good to raise an error as it is an application error, and not a user error. However, for APIs, this will not work because we do not have any control anymore on what values get sent to the server.

When the controller creates the user, instead of adding a validation error to the record, it raises an exception. How to avoid this?

In case anyone wants a hack, here is what I came up with.

Validate Forms

This rule has a few exceptions: It’s helpful to validate inline as the user is typing when creating a password (to check whether the password meets complexity requirements), when creating a user name (to check whether a name is available) and when typing a message with a character limit.

Ideally, inline validation messages should appear around 500 to 1000 milliseconds after the user has stopped typing or after they’ve moved to the next field.

Due to our emotional distress measure having little prior validation, and our physical distress measure being entirely new, we first provide data to support the appropriateness of the two measures.

Negative values included when assessing air quality In computing average pollutant concentrations, EPA includes recorded values that are below zero. EPA advised that this is consistent with NEPM AAQ procedures. Logically, however, the lowest possible value for air pollutant concentrations is zero. Either it is present, even if in very small amounts, or it is not. Negative values are an artefact of the measurement and recording process. Leaving negative values in the data introduces a negative bias, which potentially under represents actual concentrations of pollutants. We noted a considerable number of negative values recorded. For example, in 2016, negative values comprised 5.3 per cent of recorded hourly PM2.5 values, and 1.3 per cent of hourly PM10 values. When we excluded negative values from the calculation of one‐day averages, there were five more exceedance days for PM2.5 and one more for PM10 during 2016.

we can generate cross-validated predictions of the test scores with precision comparable to the gold-standard test–retest reliabilities.

It is clear from the use of ES2 and RMG-II cell lines that the Atlas Antibodies ARID1A antibody is specific for ARID1A in both Western blots and formalin-fixed paraffin embedded preparations of human origin and, coupled with the literature evidence, that it is validated in human tissue.

A No Primary antibody control (NPA) showed no staining in the epithelial or nuclear compartment (Figure 3B; Dataset e).

There was no cytoplasmic or extracellular stromal background staining present and the antibody titrated successfully losing the intensity of staining, as expected

Control slides, omitting the primary antibody, were negative except for the ER2 condition in the RMG-II cell pellet where a weak cytoplasmic background could be seen (Figure 2; Dataset d). Thus there was minimal background inherent in the staining procedure. It was therefore determined that the antibody showed specificity for formalin-fixed paraffin embedded tissues and could be run on murine tissue.

Using Western blot and IHC on murine wild-type and knockout tissue we have demonstrated that this antibody to ARID1A correctly stains murine tissue by immunohistochemistry.