CLASP Security Principles
This is a principle or a set of principles. To view all principles, please see the Principle Category page.
This CLASP Resource is meant as a set of basic principles for all members of your application-security project.
Ethics in Secure-Software Development
Software development organizations should behave ethically as a whole, but should not expect that their individual components will.
In so far as security goes, it is ethical not to expose a user to security risks that are known and will not be obvious to the user, without clearly informing the user of those risks (and preferably, mitigation strategies).
Additionally, if you have a system that is compromised on which user data resides, it is ethical to inform users of the breach in privacy. If the data resides in the state of California, this is required by law. Similar regulations may apply in other jurisdictions.
Do not expect that all other people on the development team will be ethical. Insiders play a significant factor in over 50% of corporate security breaches. Particularly at risks are those employees that are silently disgruntled or have recently left the company.
Insider Threats as the Weak Link
Most development organizations overlook “insider” risks — i.e., those users with inside access to the application, whether it be in deployment or development. For example, when planning for deployments it is easy to assume “a firewall will be there,” although, even when true, there are many techniques for circumventing a firewall.
Most development organizations completely ignore the risks from the guy in the next cube or on the next floor, the risks from the secretaries and the janitors, the risks from those who have recently quit or been fired. This, despite yearly numbers from the Computer Crime and Security Survey performed by the Computer Security Institute and the FBI, which shows that over half of all security incidents have an inside angle.
This suggests that trusting the people around you isn’t good enough. Not only might people be disgruntled or susceptible to bribe that you may not expect, but people are often susceptible to accidentally giving insider help by falling victim to social engineering attacks.
Social engineering is when an attacker uses his social skills (generally involving deception) to meet his security ends. For example, he may convince technical support that he is a particular user who has forgotten his password, and get the password changed over the phone. This is why many people have moved to systems where passwords can be reset automatically only using a “secret question” — although secret questions are a bit too repetitive... if someone is being targeted, it is often easy to figure out the mother’s maiden name, the person’s favorite color, and the name of his or her pets.
Assume the Network is Compromised
There are many categories of attack that can be launched by attackers with access to any network media that can see application traffic. Many people assume wrongly that such attacks are not feasible, assuming that it is “difficult to get in the middle of network communications,” especially when most communications are from ISP to ISP.
One misconception is that an attacker actually needs to “be in the middle” for a network attack to be successful. Ethernet is a shared medium, and it turns out that attacks can be launched if the bad guy is on one of the shared segments that will see the traffic. Generally, the greatest risk lies in the local networks that the endpoints use.
Many people think that plugging into a network via a switch will prevent against the threat on the local network. Unfortunately, that is not true, as switches can have their traffic intercepted and monitored using a technique called ARP spoofing. And even if this problem were easily addressed, there are always attacks on the physical media that tend to be easy to perform.
As for router infrastructure, remember that most routers run software. For example, Cisco’s routers run IOS, an operating system written in C that has had exploitable conditions found in it in the past. It may occasionally be reasonable for an attacker to truly be “in the middle.”
Another misconception is that network-level attacks are difficult to perform. There are tools that easily automate them. For example, “dsniff” will automate many attacks, including man-in-the-middle eavesdropping and ARP spoofing.
Well known network-level threats include the following:
- Eavesdropping — Even when using cryptography, eavesdropping may be possible when not performing proper authentication, using a man-in-the-middle attack.
- Tampering — An attacker can change data on the wire. Even if the data is encrypted, it may be possible to make significant changes to the data without being able to decrypt it. Tampering is best thwarted by performing ongoing message authentication (MACing), provided by most high-level protocols, such as SSL/TLS.
- Spoofing — Traffic can be forged so that it appears to come from a different source address than the one from which it actually comes. This will thwart authentication systems that rely exclusively on IP addresses and/or DNS names for authentication.
- Hijacking — An extension of spoofing, in which established connections can be taken over, allowing the attacker to enter an already established session without having to authenticate. This can be thwarted with ongoing message authentication, which is provided by most high-level protocols, such as SSL/TLS.
- Observing — It is possible to give away security-critical information even when a network connection is confidentiality-protected through encryption. For example, the mere fact that two particular hosts are talking may give away significant information, as can the timing of traffic. These are generally examples of covert channels (non-obvious communication paths), which tend to be the most difficult problem in the security space.
Minimize Attack Surface
For a large application, a rough yet reliable metric for determining overall risk is to measure the number of input points that the application has — i.e., attack surface. The notion is that more points of entry into the application provides more avenues for an attacker to find a weakness.
Of course, any such metric must consider the accessibility of the input point. For example, many applications are developed for a threat model where the local environment is trusted. In this case, having a large number of local input points such as configuration files, registry keys, user input, etc., should be considered far less worrisome than making several external network connections.
Collapsing functionality that previously was spread across several ports onto a single port does not always help reduce attack surface, particularly when the single port exports all the same functionality, with an infrastructure that performs basic switching. The effective attack surface is the same unless the actual functionality is somehow simplified. Since underlying complexity clearly plays a role, metrics based on attack surface should not be used as the only means access control should be mandatory of analyzing risks in a piece of software.
A system’s default setting should not expose users to unnecessary risks and should be as secure as possible. This means that all security functionality should be enabled by default, and all optional features which entail any security risk should be disabled by default.
It also means that — if there is some sort of failure in the system — the behavior should not cause the system to behave in an insecure manner (the “fail-safe” principle). For example, if a connection cannot be established over SSL, it is not a good idea to try to establish a plaintext connection.
The “secure-by-default” philosophy does not interact well with usability since it is far simpler for the user to make immediate use of a system if all functionality is enabled. He can make use of functionality which is needed and ignore the functionality that is not.
However, attackers will not ignore this functionality. A system released with an insecure default configuration ensures that the vast majority of systems-in-the-wild are vulnerable. In many circumstances, it can even become difficult to patch a system before it is compromised.
Therefore, if there are significant security risks that the user is not already accepting, you should prefer a secure-by-default configuration. If not, at least alert the user to the risks ahead of time and point him to documentation on mitigation strategies.
Note that, in a secure-by-default system, the user will have to explicitly enable any functionality that increases his risk. Such operations should be relatively hidden (e.g., in an “advanced” preference pane) and should make the risks in disabling the functionality readily apparent.
The principle of defense-in-depth is that redundant security mechanisms increase security. If one mechanism fails, perhaps the other one will still provide the necessary security. For example, it is not a good idea to rely on a firewall to provide security for an internal-use-only application, as firewalls can usually be circumvented by a determined attacker (even if it requires a physical attack or a social engineering attack of some sort).
Implementing a defense-in-depth strategy can add to the complexity of an application, which runs counter to the “simplicity” principle often practiced in security. That is, one could argue that new protection functionality adds additional complexity that might bring new risks with it. The risks need to be weighed. For example, a second mechanism may make no sense when the first mechanism is believed to be 100% effective; therefore, there is not much reason for introducing the additional solution, which may pose new risks. But usually the risks in additional complexity are minimal compared to the risk the protection mechanism seeks to reduce.
Principles for Reducing Exposure
Submarines employ a trick that makes them far less risky to inhabit. Assume that you are underwater on a sub when the hull bursts right by you. You actually have a reasonable chance of survival, because the ship is broken up into separate airtight compartments. If one compartment takes on water, it can be sealed off from the rest of the compartments.
Compartmentalization is a good principle to keep in mind when designing software systems. The basic idea is to try to contain damage if something does goes wrong. Another principle is that of least privilege, which states that privileges granted to a user should be limited to only those privileges necessary to do what that user needs to do. For example, least privilege argues that you should not run your program with administrative privileges, if at all possible. Instead, you should run it as a lesser user with just enough privileges to do the job, and no more.
Another relevant principle is to minimize windows of vulnerability. This means that — when risks must be introduced — they should be introduced for as short a time as possible (a corollary of this is “insecure bootstrapping”). In the context of privilege, it is could to account for which privileges a user can obtain, but only grant them when the situation absolutely merits. That supports the least privilege principle by granting the user privileges only when necessary, and revoking them immediately after use.
When the resources you are mitigating access in order to live outside your application, these principles are usually easier to apply with operational controls than with controls you build into your own software. However, one highly effective technique for enforcing these principles is the notion of privilege separation. The idea is that an application is broken up into two portions, the privileged core and the main application. The privileged core has as little functionality as absolutely possible so that it can be well audited. Its only purposes are as follows:
- Authenticate new connections and spawn off unprivileged main processes to handle those connections.
- Mediate access to those resources which the unprivileged process might legitimately get to access. That is, the core listens to requests from the children, determines whether they are valid, and then executes them on behalf of the unprivileged process.
This technique compartmentalizes each user of the system into its own process and completely removes all access to privileges, except for those privileges absolutely necessary, and then grants those privileges indirectly, only at the point where it is necessary.
The Insecure-Bootstrapping Principle
Insecure bootstrapping is the principle that — if you need to use an insecure communication channel for anything — you should use it to bootstrap a secure communication channel so that you do not need to use an insecure channel again.
For example, SSH is a protocol that provides a secure channel after the client and server have authenticated each other. Since it does not use a public key infrastructure the first time the client connects, it generally will not have the server credentials. The server sends its credentials, and the client just blindly accepts that they’re the right ones. Clearly, if an attacker can send his own credentials, he can masquerade as the server or launch a man-in-the-middle attack.
But, the SSH client remembers the credentials. If the credentials remain the same, and the first connection was secure, then subsequent connections are secure. If the credentials change, then something is wrong — i.e., either an attack is being waged, or the server credentials have changed — and SSH clients will generally alert the user.
Of course, it is better not to use an insecure communication channel at all, if it can be avoided.
If a program is liberal in what it accepts, it often risks an attacker finding an input that has negative security implications. Several major categories of software security problems are ultimately input validation problems — including buffer overflows, SQL injection attacks, and command-injection attacks.
Data input to a program is either valid or invalid. What defines valid can be dependent on the semantics of the program. Good security practice is to definitively identify all invalid data before any action on the data is taken. And, if data is invalid, one should act appropriately.
Where to perform input validation
There are many levels at which one can perform input validation. Common places include:
- Use — all places in the code where data (particularly data of external origin) gets used.
- Unit boundaries — i.e., individual components, modules, or functions;
- Trust boundaries — i.e., on a per-executable basis.
- Protocol parsing — When the network protocol gets interpreted.
- Application entry points — e.g., just before or just after passing data to an application, such as a validation engine in a web server for a web service.
- Network — i.e., a traditional intrusion detection system (IDS).
Validating at use is generally quite error-prone because it is easy to forget to insert a check. This is still true, but less so when validating at unit boundaries. Going up the line, validation becomes less error prone. However, at higher levels, it gets harder and harder to make accurate checks because there is less and less context readily available to make a decision with.
At a bare minimum, input validation should be performed at unit boundaries, preferably using a structured technique such as design-by-contract. Validating at other levels provides defense-in-depth to help handle the case where a check is forgotten at a lower level.
Ways in which data can be invalid
At a high level, invalid data is anything that does not meet the strictest possible definition of valid. It does not just encompass malformed data, it encompasses missing data and out-of-order data (e.g., data used in a capture-replay attack).
There are four different contexts in which data can be invalid:
- Sender — Data is invalid if it did not originate from an authentic source.
- Tokens — Data in network protocols are generally broken up into atomic units called tokens, which often map to concrete data types (e.g., numbers, zip codes, and strings). An invalid token is one that is an invalid value for all token types known to a system.
- Syntax — Protocols accept messages as valid based on a protocol syntax, which is usually defined in terms of tokens. An invalid message is one that should not be accepted as part of the protocol.
- Semantics — Even when a message satisfies syntax requirements, it may be semantically invalid.
How to determine input validity
Data validity must be evaluated in each of the four contexts described above. For example, a valid sender can send bad tokens. Good tokens can be combined in syntactically invalid ways. And, otherwise valid messages can make no valid sense in terms of the program’s semantics.
At a high-level, there are three approaches to providing data validity:
- Black-listing — Widely considered bad practice in all cases, one validates based on a policy that explicitly defines bad values. All other data is assumed to be valid, but in practice, it often is not (or should not be).
- White-listing — One validates based on a precise description of what valid data entails (a policy). If the policy is correct, this prevents accidentally allowing maliciously invalid data. The risks are that the policy will not be correct, which may result not only in allowing bad data but also in disallowing some valid data.
- Cryptographic validation — One uses cryptography to demonstrate validity of the data.
Handling each input validation context involves a separate strategy:
- The sender can, in the general case, only be validated adequately using cryptographic message authentication.
- Tokens are generally validated using a simple state machine describing valid tokens (often implemented with regular expressions).
- Syntax is generally validated using a standard language parser, such as a recursive decent parser or a parser generated by a parser generator.
- Semantics are generally validated at the highest boundary at which all of the semantic data needed to make a decision is available. Message-ordering omission is best validated cryptographically along with sender authentication.
Protocol-specific semantics are often best validated in the context of a parser generated from a specification. In this case, semantics should be validated in the production associated with a single syntactic rule. When not enough semantic data is available at this level, semantic validation is best performed using a design-by-contract approach.
Actions to perform when invalid data is found
There are three classes of action one can take when invalid data is identified:
- Error — This includes fatal errors and non-fatal errors.
- Record — This includes logging errors and sending notifications of errors to interested parties.
- Modify — This includes filtering data or replacing data with default values.
These three classes are orthogonal, meaning that the decision to do any one is independent from the others. One can easily perform all three classes of action.