C-I-A (confidentiality, integrity, and availability)

The following is an excerpt from the book Designing Secure Software: A Guide for Developers by Loren Kohnfelder, Copyright 2022, No Starch Press

We traditionally build software security on three basic principles of information security: confidentiality, integrity, and availability. Formulated around the fundamentals of data protection, the meanings of the three pillars are intuitive:

Confidentiality: Allow only authorized data access—don’t leak information.

Integrity: Maintain data accurately—don’t allow unauthorized modification or deletion.

Availability: Preserve the availability of data—don’t allow significant delays or unauthorized shutdowns.

Each of these brief definitions describes the goal and defenses against its subversion. In reviewing designs, it’s often helpful to think of ways one might undermine security, and work back to defensive measures.

All three components of C-I-A represent ideals, and it’s crucial to avoid insisting on perfection. For example, an analysis of even solidly encrypted network traffic could allow a determined eavesdropper to deduce something about the communications between two endpoints, like the volume of data exchanged. Technically, this exchange of data weakens the confidentiality of interaction between the endpoints; but for practical purposes, we can’t fix it without taking extreme measures, and usually the risk is minor enough to be safely ignored. (One way to conceal the fact of communication is for endpoints to always exchange a constant volume of data, adding dummy packets as needed when actual traffic is lower.)

Notice that authorization is inherent in each component of C-I-A, which mandates only the right disclosures, modifications of data, or controls of availability. What constitutes “right” is an important detail, and an authorization policy needs to specify that, but it isn’t part of these fundamental data protection primitive concepts.


Maintaining confidentiality means disclosing private information in only an authorized manner. This sounds simple, but in practice it involves a number of complexities.

First, it’s important to carefully identify what information to consider private. Design documents should make this distinction clear. While what counts as sensitive might sometimes seem obvious, it’s actually surprising how people’s opinions vary, and without an explicit specification, we risk misunderstanding. The safest assumption is to treat all externally collected information as private by default, until declared otherwise by an explicit policy that explains how and why the designation can be relaxed. Here are some oft-overlooked reasons to treat data as private:

  • An end user might naturally expect their data to be private, unless informed otherwise, even if revealing it isn’t harmful.

  • People might enter sensitive information into a text field intended for a different use.

  • Information collection, handling, and storage might be subject to laws and regulations that many are unaware of. (For example, if Europeans browse your website, it may be subject to EU law, such as the General Data Protection Regulation.)

When handling private information, determine what constitutes proper access. Deciding when and how to disclose information is ultimately a trust decision, and it’s worth not only spelling out the rules, but also explaining the subjective choices behind those rules.

Compromises of confidentiality happen on a spectrum. In a complete disclosure, attackers acquire an entire dataset, including metadata. At the lower end of the spectrum might be a minor disclosure of information, such as an internal error message or similar leak of no real consequence. As an example of a partial disclosure, consider the practice of assigning sequential numbers to new customers: a wily competitor can sign up as a new customer and get a new customer number from time to time, then compute the successive differences to learn the numbers of customers acquired during each interval. Any leakage details about protected data is to some degree a confidentiality compromise.

It’s so easy to underestimate the potential value of minor disclosures. Attackers might put data to use in a completely different way than the developers originally intended, and combining tiny bits of information can provide more powerful insights than any of the individual parts on their own. Learning someone’s ZIP code might not tell you much, but if you also know their approximate age and that they’re an MD, you could perhaps combine this information to identify the individual in a sparsely populated area – a process known as deanonymization or reidentification. By analyzing a supposedly anonymized dataset published by Netflix, researchers were able to match numerous user accounts to IMDb accounts: it turns out that your favorite movies are a very effective means of unique personal identification.


Integrity, used in an information security context, is simply the authenticity and accuracy of data, kept safe from unauthorized tampering or removal. In addition to protecting against unauthorized modification, an accurate record of the provenance of data—the original source, and any authorized changes made—can be an important, and stronger, assurance of integrity.

One classic defense against many tampering attacks is to preserve versions of critical data and record their provenance. Simply put, keep good backups. Incremental backups can be excellent mitigations because they’re simple and efficient to put in place and provide a series of snapshots that detail exactly what data changed, and when. However, the need for integrity goes far beyond the protection of data, and often includes ensuring the integrity of components, server logs, software source code and versions, and other forensic information necessary to determine the original source of tampering when problems occur. In addition to limited administrative access controls, secure digests (similar to checksums) and digital signatures are also strong integrity checks.

Bear in mind that tampering can happen in many different ways, not necessarily by modifying data in storage. For instance, in a web application, tampering might happen on the client side, on the wire between the client and server, by tricking an authorized party into making a change, by modi- fying a script on the page, or in many other ways.


Attacks on availability are a sad reality of the internet-connected world and can be among the most difficult to defend against. In the simplest cases, the attacker may just send an exceptionally heavy load of traffic to the server, overwhelming it with what looks like valid uses of the service. This principle implies that information is temporarily unavailable; while data that is perma- nently lost is also unavailable, this is generally considered to be fundamentally a compromise of integrity.

Anonymous denial-of-service (DoS) attacks, often for ransom, threaten any internet service, posing a difficult challenge. To best defend against such attacks, host on large-scale services with infrastructure that stands up to heavy loads, and maintain the flexibility to move infrastructure quickly in the event of problems. Nobody knows how common or costly DoS attacks really are, since many victims resolve these incidents privately. But without a doubt, you should create detailed plans in advance to prepare for such incidents.

Many other kinds of availability threats are possible as well. For a web server, a malformed request that triggers a bug, causing a crash or infinite loop, can devastate its service. Other attacks can also overload the storage, computation, or communication capacity of an application, or perhaps use patterns that break the effectiveness of caching, all of which pose serious issues. Unauthorized destruction of software, configuration, or data (even with backup, delays can result) also can adversely impact availability.