Tag Archives: protocols

Oblivious DNS-over-HTTPS

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2020/12/oblivious-dns-over-https.html

This new protocol, called Oblivious DNS-over-HTTPS (ODoH), hides the websites you visit from your ISP.

Here’s how it works: ODoH wraps a layer of encryption around the DNS query and passes it through a proxy server, which acts as a go-between the internet user and the website they want to visit. Because the DNS query is encrypted, the proxy can’t see what’s inside, but acts as a shield to prevent the DNS resolver from seeing who sent the query to begin with.

IETF memo.

The paper:

Abstract: The Domain Name System (DNS) is the foundation of a human-usable Internet, responding to client queries for host-names with corresponding IP addresses and records. Traditional DNS is also unencrypted, and leaks user information to network operators. Recent efforts to secure DNS using DNS over TLS (DoT) and DNS over HTTPS (DoH) havebeen gaining traction, ostensibly protecting traffic and hiding content from on-lookers. However, one of the criticisms ofDoT and DoH is brought to bear by the small number of large-scale deployments (e.g., Comcast, Google, Cloudflare): DNS resolvers can associate query contents with client identities in the form of IP addresses. Oblivious DNS over HTTPS (ODoH) safeguards against this problem. In this paper we ask what it would take to make ODoH practical? We describe ODoH, a practical DNS protocol aimed at resolving this issue by both protecting the client’s content and identity. We implement and deploy the protocol, and perform measurements to show that ODoH has comparable performance to protocols like DoH and DoT which are gaining widespread adoption,while improving client privacy, making ODoH a practical privacy enhancing replacement for the usage of DNS.

Slashdot thread.

Good-bye ESNI, hello ECH!

Post Syndicated from Christopher Patton original https://blog.cloudflare.com/encrypted-client-hello/

Good-bye ESNI, hello ECH!

Good-bye ESNI, hello ECH!

Most communication on the modern Internet is encrypted to ensure that its content is intelligible only to the endpoints, i.e., client and server. Encryption, however, requires a key and so the endpoints must agree on an encryption key without revealing the key to would-be attackers. The most widely used cryptographic protocol for this task, called key exchange, is the Transport Layer Security (TLS) handshake.

In this post we’ll dive into Encrypted Client Hello (ECH), a new extension for TLS that promises to significantly enhance the privacy of this critical Internet protocol. Today, a number of privacy-sensitive parameters of the TLS connection are negotiated in the clear. This leaves a trove of metadata available to network observers, including the endpoints’ identities, how they use the connection, and so on.

ECH encrypts the full handshake so that this metadata is kept secret. Crucially, this closes a long-standing privacy leak by protecting the Server Name Indication (SNI) from eavesdroppers on the network. Encrypting the SNI secret is important because it is the clearest signal of which server a given client is communicating with. However, and perhaps more significantly, ECH also lays the groundwork for adding future security features and performance enhancements to TLS while minimizing their impact on the privacy of end users.

ECH is the product of close collaboration, facilitated by the IETF, between academics and the tech industry leaders, including Cloudflare, our friends at Fastly and Mozilla (both of whom are the affiliations of co-authors of the standard), and many others. This feature represents a significant upgrade to the TLS protocol, one that builds on bleeding edge technologies, like DNS-over-HTTPS, that are only now coming into their own. As such, the protocol is not yet ready for Internet-scale deployment. This article is intended as a sign post on the road to full handshake encryption.

Background

The story of TLS is the story of the Internet. As our reliance on the Internet has grown, so the protocol has evolved to address ever-changing operational requirements, use cases, and threat models. The client and server don’t just exchange a key: they negotiate a wide variety of features and parameters: the exact method of key exchange; the encryption algorithm; who is authenticated and how; which application layer protocol to use after the handshake; and much, much more. All of these parameters impact the security properties of the communication channel in one way or another.

SNI is a prime example of a parameter that impacts the channel’s security. The SNI extension is used by the client to indicate to the server the website it wants to reach. This is essential for the modern Internet, as it’s common nowadays for many origin servers to sit behind a single TLS operator. In this setting, the operator uses the SNI to determine who will authenticate the connection: without it, there would be no way of knowing which TLS certificate to present to the client. The problem is that SNI leaks to the network the identity of the origin server the client wants to connect to, potentially allowing eavesdroppers to infer a lot of information about their communication. (Of course, there are other ways for a network observer to identify the origin — the origin’s IP address, for example. But co-locating with other origins on the same IP address makes it much harder to use this metric to determine the origin than it is to simply inspect the SNI.)

Although protecting SNI is the impetus for ECH, it is by no means the only privacy-sensitive handshake parameter that the client and server negotiate. Another is the ALPN extension, which is used to decide which application-layer protocol to use once the TLS connection is established. The client sends the list of applications it supports — whether it’s HTTPS, email, instant messaging, or the myriad other applications that use TLS for transport security — and the server selects one from this list, and sends its selection to the client. By doing so, the client and server leak to the network a clear signal of their capabilities and what the connection might be used for.

Some features are so privacy-sensitive that their inclusion in the handshake is a non-starter. One idea that has been floated is to replace the key exchange at the heart of TLS with password-authenticated key-exchange (PAKE). This would allow password-based authentication to be used alongside (or in lieu of) certificate-based authentication, making TLS more robust and suitable for a wider range of applications. The privacy issue here is analogous to SNI: servers typically associate a unique identifier to each client (e.g., a username or email address) that is used to retrieve the client’s credentials; and the client must, somehow, convey this identity to the server during the course of the handshake. If sent in the clear, then this personally identifiable information would be easily accessible to any network observer.

A necessary ingredient for addressing all of these privacy leaks is handshake encryption, i.e., the encryption of handshake messages in addition to application data. Sounds simple enough, but this solution presents another problem: how do the client and server pick an encryption key if, after all, the handshake is itself a means of exchanging a key? Some parameters must be sent in the clear, of course, so the goal of ECH is to encrypt all handshake parameters except those that are essential to completing the key exchange.

In order to understand ECH and the design decisions underpinning it, it helps to understand a little bit about the history of handshake encryption in TLS.

Handshake encryption in TLS

TLS had no handshake encryption at all prior to the latest version, TLS 1.3. In the wake of the Snowden revelations in 2013, the IETF community began to consider ways of countering the threat that mass surveillance posed to the open Internet. When the process of standardizing TLS 1.3 began in 2014, one of its design goals was to encrypt as much of the handshake as possible. Unfortunately, the final standard falls short of full handshake encryption, and several parameters, including SNI, are still sent in the clear. Let’s take a closer look to see why.

The TLS 1.3 protocol flow is illustrated in Figure 1. Handshake encryption begins as soon as the client and server compute a fresh shared secret. To do this, the client sends a key share in its ClientHello message, and the server responds in its ServerHello with its own key share. Having exchanged these shares, the client and server can derive a shared secret. Each subsequent handshake message is encrypted using the handshake traffic key derived from the shared secret. Application data is encrypted using a different key, called the application traffic key, which is also derived from the shared secret. These derived keys have different security properties: to emphasize this, they are illustrated with different colors.

The first handshake message that is encrypted is the server’s EncryptedExtensions. The purpose of this message is to protect the server’s sensitive handshake parameters, including the server’s ALPN extension, which contains the application selected from the client’s ALPN list. Key-exchange parameters are sent unencrypted in the ClientHello and ServerHello.

Good-bye ESNI, hello ECH!
Figure 1: The TLS 1.3 handshake.

All of the client’s handshake parameters, sensitive or not, are sent in the ClientHello. Looking at Figure 1, you might be able to think of ways of reworking the handshake so that some of them can be encrypted, perhaps at the cost of additional latency (i.e., more round trips over the network). However, extensions like SNI create a kind of “chicken-and-egg” problem.

The client doesn’t encrypt anything until it has verified the server’s identity (this is the job of the Certificate and CertificateVerify messages) and the server has confirmed that it knows the shared secret (the job of the Finished message). These measures ensure the key exchange is authenticated, thereby preventing monster-in-the-middle (MITM) attacks in which the adversary impersonates the server to the client in a way that allows it to decrypt messages sent by the client.  Because SNI is needed by the server to select the certificate, it needs to be transmitted before the key exchange is authenticated.

In general, ensuring confidentiality of handshake parameters used for authentication is only possible if the client and server already share an encryption key. But where might this key come from?

Full handshake encryption in the early days of TLS 1.3. Interestingly, full handshake encryption was once proposed as a core feature of TLS 1.3. In early versions of the protocol (draft-10, circa 2015), the server would offer the client a long-lived public key during the handshake, which the client would use for encryption in subsequent handshakes. (This design came from a protocol called OPTLS, which in turn was borrowed from the original QUIC proposal.) Called “0-RTT”, the primary purpose of this mode was to allow the client to begin sending application data prior to completing a handshake. In addition, it would have allowed the client to encrypt its first flight of handshake messages following the ClientHello, including its own EncryptedExtensions, which might have been used to protect the client’s sensitive handshake parameters.

Ultimately this feature was not included in the final standard (RFC 8446, published in 2018), mainly because its usefulness was outweighed by its added complexity. In particular, it does nothing to protect the initial handshake in which the client learns the server’s public key. Parameters that are required for server authentication of the initial handshake, like SNI, would still be transmitted in the clear.

Nevertheless, this scheme is notable as the forerunner of other handshake encryption mechanisms, like ECH, that use public key encryption to protect sensitive ClientHello parameters. The main problem these mechanisms must solve is key distribution.

Before ECH there was (and is!) ESNI

The immediate predecessor of ECH was the Encrypted SNI (ESNI) extension. As its name implies, the goal of ESNI was to provide confidentiality of the SNI. To do so, the client would encrypt its SNI extension under the server’s public key and send the ciphertext to the server. The server would attempt to decrypt the ciphertext using the secret key corresponding to its public key. If decryption were to succeed, then the server would proceed with the connection using the decrypted SNI. Otherwise, it would simply abort the handshake. The high-level flow of this simple protocol is illustrated in Figure 2.

Good-bye ESNI, hello ECH!
Figure 2: The TLS 1.3 handshake with the ESNI extension. It is identical to the TLS 1.3 handshake, except the SNI extension has been replaced with ESNI.

For key distribution, ESNI relied on another critical protocol: Domain Name Service (DNS). In order to use ESNI to connect to a website, the client would piggy-back on its standard A/AAAA queries a request for a TXT record with the ESNI public key. For example, to get the key for crypto.dance, the client would request the TXT record of _esni.crypto.dance:

$ dig _esni.crypto.dance TXT +short
"/wGuNThxACQAHQAgXzyda0XSJRQWzDG7lk/r01r1ZQy+MdNxKg/mAqSnt0EAAhMBAQQAAAAAX67XsAAAAABftsCwAAA="

The base64-encoded blob contains an ESNI public key and related parameters such as the encryption algorithm.

But what’s the point of encrypting SNI if we’re just going to leak the server name to network observers via a plaintext DNS query? Deploying ESNI this way became feasible with the introduction of DNS-over-HTTPS (DoH), which enables encryption of DNS queries to resolvers that provide the DoH service (1.1.1.1 is an example of such a service.). Another crucial feature of DoH is that it provides an authenticated channel for transmitting the ESNI public key from the DoH server to the client. This prevents cache-poisoning attacks that originate from the client’s local network: in the absence of DoH, a local attacker could prevent the client from offering the ESNI extension by returning an empty TXT record, or coerce the client into using ESNI with a key it controls.

While ESNI took a significant step forward, it falls short of our goal of achieving full handshake encryption. Apart from being incomplete — it only protects SNI — it is vulnerable to a handful of sophisticated attacks, which, while hard to pull off, point to theoretical weaknesses in the protocol’s design that need to be addressed.

ESNI was deployed by Cloudflare and enabled by Firefox, on an opt-in basis, in 2018, an  experience that laid bare some of the challenges with relying on DNS for key distribution. Cloudflare rotates its ESNI key every hour in order to minimize the collateral damage in case a key ever gets compromised. DNS artifacts are sometimes cached for much longer, the result of which is that there is a decent chance of a client having a stale public key. While Cloudflare’s ESNI service tolerates this to a degree, every key must eventually expire. The question that the ESNI protocol left open is how the client should proceed if decryption fails and it can’t access the current public key, via DNS or otherwise.

Another problem with relying on DNS for key distribution is that several endpoints might be authoritative for the same origin server, but have different capabilities. For example, a request for the A record of “example.com” might return one of two different IP addresses, each operated by a different CDN. The TXT record for “_esni.example.com” would contain the public key for one of these CDNs, but certainly not both. The DNS protocol does not provide a way of atomically tying together resource records that correspond to the same endpoint. In particular, it’s possible for a client to inadvertently offer the ESNI extension to an endpoint that doesn’t support it, causing the handshake to fail. Fixing this problem requires changes to the DNS protocol. (More on this below.)

The future of ESNI. In the next section, we’ll describe the ECH specification and how it addresses the shortcomings of ESNI. Despite its limitations, however, the practical privacy benefit that ESNI provides is significant. Cloudflare intends to continue its support for ESNI until ECH is production-ready.

The ins and outs of ECH

The goal of ECH is to encrypt the entire ClientHello, thereby closing the gap left in TLS 1.3 and ESNI by protecting all privacy-sensitive handshake-parameters. Similar to ESNI, the protocol uses a public key, distributed via DNS and obtained using DoH, for encryption during the client’s first flight. But ECH has improvements to key distribution that make the protocol more robust to DNS cache inconsistencies. Whereas the ESNI server aborts the connection if decryption fails, the ECH server attempts to complete the handshake and supply the client with a public key it can use to retry the connection.

But how can the server complete the handshake if it’s unable to decrypt the ClientHello? As illustrated in Figure 3, the ECH protocol actually involves two ClientHello messages: the ClientHelloOuter, which is sent in the clear, as usual; and the ClientHelloInner, which is encrypted and sent as an extension of the ClientHelloOuter. The server completes the handshake with just one of these ClientHellos: if decryption succeeds, then it proceeds with the ClientHelloInner; otherwise, it proceeds with the ClientHelloOuter.

Good-bye ESNI, hello ECH!
Figure 3: The TLS 1.3 handshake with the ECH extension.

The ClientHelloInner is composed of the handshake parameters the client wants to use for the connection. This includes sensitive values, like the SNI of the origin server it wants to reach (called the backend server in ECH parlance), the ALPN list, and so on. The ClientHelloOuter, while also a fully-fledged ClientHello message, is not used for the intended connection. Instead, the handshake is completed by the ECH service provider itself (called the client-facing server), signaling to the client that its intended destination couldn’t be reached due to decryption failure. In this case, the service provider also sends along the correct ECH public key with which the client can retry handshake, thereby “correcting” the client’s configuration. (This mechanism is similar to how the server distributed its public key for 0-RTT mode in the early days of TLS 1.3.)

At a minimum, both ClientHellos must contain the handshake parameters that are required for a server-authenticated key-exchange. In particular, while the ClientHelloInner contains the real SNI, the ClientHelloOuter also contains an SNI value, which the client expects to verify in case of ECH decryption failure (i.e., the client-facing server). If the connection is established using the ClientHelloOuter, then the client is expected to immediately abort the connection and retry the handshake with the public key provided by the server. It’s not necessary that the client specify an ALPN list in the ClientHelloOuter, nor any other extension used to guide post-handshake behavior. All of these parameters are encapsulated by the encrypted ClientHelloInner.

This design resolves — quite elegantly, I think — most of the challenges for securely deploying handshake encryption encountered by earlier mechanisms. Importantly, the design of ECH was not conceived in a vacuum. The protocol reflects the diverse perspectives of the IETF community, and its development dovetails with other IETF standards that are crucial to the success of ECH.

The first is an important new DNS feature known as the HTTPS resource record type. At a high level, this record type is intended to allow multiple HTTPS endpoints that are authoritative for the same domain name to advertise different capabilities for TLS. This makes it possible to rely on DNS for key distribution, resolving one of the deployment challenges uncovered by the initial ESNI deployment. For a deep dive into this new record type and what it means for the Internet more broadly, check out Alessandro Ghedini’s recent blog post on the subject.

The second is the CFRG’s Hybrid Public Key Encryption (HPKE) standard, which specifies an extensible framework for building public key encryption schemes suitable for a wide variety of applications. In particular, ECH delegates all of the details of its handshake encryption mechanism to HPKE, resulting in a much simpler and easier-to-analyze specification. (Incidentally, HPKE is also one of the main ingredients of Oblivious DNS-over-HTTPS.

The road ahead

The current ECH specification is the culmination of a multi-year collaboration. At this point, the overall design of the protocol is fairly stable. In fact, the next draft of the specification will be the first to be targeted for interop testing among implementations. Still, there remain a number of details that need to be sorted out. Let’s end this post with a brief overview of the road ahead.

Resistance to traffic analysis

Ultimately, the goal of ECH is to ensure that TLS connections made to different origin servers behind the same ECH service provider are indistinguishable from one another. In other words, when you connect to an origin behind, say, Cloudflare, no one on the network between you and Cloudflare should be able to discern which origin you reached, or which privacy-sensitive handshake-parameters you and the origin negotiated. Apart from an immediate privacy boost, this property, if achieved, paves the way for the deployment of new features for TLS without compromising privacy.

Encrypting the ClientHello is an important step towards achieving this goal, but we need to do a bit more. An important attack vector we haven’t discussed yet is traffic analysis. This refers to the collection and analysis of properties of the communication channel that betray part of the ciphertext’s contents, but without cracking the underlying encryption scheme. For example, the length of the encrypted ClientHello might leak enough information about the SNI for the adversary to make an educated guess as to its value (this risk is especially high for domain names that are either particularly short or particularly long). It is therefore crucial that the length of each ciphertext is independent of the values of privacy-sensitive parameters. The current ECH specification provides some mitigations, but their coverage is incomplete. Thus, improving ECH’s resistance to traffic analysis is an important direction for future work.

The spectre of ossification

An important open question for ECH is the impact it will have on network operations.

One of the lessons learned from the deployment of TLS 1.3 is that upgrading a core Internet protocol can trigger unexpected network behavior. Cloudflare was one of the first major TLS operators to deploy TLS 1.3 at scale; when browsers like Firefox and Chrome began to enable it on an experimental basis, they observed a significantly higher rate of connection failures compared to TLS 1.2. The root cause of these failures was network ossification, i.e., the tendency of middleboxes — network appliances between clients and servers that monitor and sometimes intercept traffic — to write software that expects traffic to look and behave a certain way. Changing the protocol before middleboxes had the chance to update their software led to middleboxes trying to parse packets they didn’t recognize, triggering software bugs that, in some instances, caused connections to be dropped completely.

This problem was so widespread that, instead of waiting for network operators to update their software, the design of TLS 1.3 was altered in order to mitigate the impact of network ossification. The ingenious solution was to make TLS 1.3 “look like” another protocol that middleboxes are known to tolerate. Specifically, the wire format and even the contents of handshake messages were made to resemble TLS 1.2. These two protocols aren’t identical, of course — a curious network observer can still distinguish between them — but they look and behave similar enough to ensure that the majority of existing middleboxes don’t treat them differently. Empirically, it was found that this strategy significantly reduced the connection failure rate enough to make deployment of TLS 1.3 viable.

Once again, ECH represents a significant upgrade for TLS for which the spectre of network ossification looms large. The ClientHello contains parameters, like SNI, that have existed in the handshake for a long time, and we don’t yet know what the impact will be of encrypting them. In anticipation of the deployment issues ossification might cause, the ECH protocol has been designed to look as much like a standard TLS 1.3 handshake as possible. The most notable difference is the ECH extension itself: if middleboxes ignore it — as they should, if they are compliant with the TLS 1.3 standard — then the rest of the handshake will look and behave very much as usual.

It remains to be seen whether this strategy will be enough to ensure the wide-scale deployment of ECH. If so, it is notable that this new feature will help to mitigate the impact of future TLS upgrades on network operations. Encrypting the full handshake reduces the risk of ossification since it means that there are less visible protocol features for software to ossify on. We believe this will be good for the health of the Internet overall.

Conclusion

The old TLS handshake is (unintentionally) leaky. Operational requirements of both the client and server have led to privacy-sensitive parameters, like SNI, being negotiated completely in the clear and available to network observers. The ECH extension aims to close this gap by enabling encryption of the full handshake. This represents a significant upgrade to TLS, one that will help preserve end-user privacy as the protocol continues to evolve.

The ECH standard is a work-in-progress. As this work continues, Cloudflare is committed to doing its part to ensure this important upgrade for TLS reaches Internet-scale deployment.

OPAQUE: The Best Passwords Never Leave your Device

Post Syndicated from Tatiana Bradley original https://blog.cloudflare.com/opaque-oblivious-passwords/

OPAQUE: The Best Passwords Never Leave your Device

OPAQUE: The Best Passwords Never Leave your Device

Passwords are a problem. They are a problem for reasons that are familiar to most readers. For us at Cloudflare, the problem lies much deeper and broader. Most readers will immediately acknowledge that passwords are hard to remember and manage, especially as password requirements grow increasingly complex. Luckily there are great software packages and browser add-ons to help manage passwords. Unfortunately, the greater underlying problem is beyond the reaches of software to solve.

The fundamental password problem is simple to explain, but hard to solve: A password that leaves your possession is guaranteed to sacrifice security, no matter its complexity or how hard it may be to guess. Passwords are insecure by their very existence.

You might say, “but passwords are always stored in encrypted format!” That would be great. More accurately, they are likely stored as a salted hash, as explained below. Even worse is that there is no way to verify the way that passwords are stored, and so we can assume that on some servers passwords are stored in cleartext. The truth is that even responsibly stored passwords can be leaked and broken, albeit (and thankfully) with enormous effort. An increasingly pressing problem stems from the nature of passwords themselves: any direct use of a password, today, means that the password must be handled in the clear.

You say, “but my password is transmitted securely over HTTPS!” This is true.

You say, “but I know the server stores my password in hashed form, secure so no one can access it!” Well, this puts a lot of faith in the server. Even so, let’s just say that yes, this may be true, too.

There remains, however, an important caveat — a gap in the end-to-end use of passwords. Consider that once a server receives a password, between being securely transmitted and securely stored, the password has to be read and processed. Yes, as cleartext!

And it gets worse — because so many are used to thinking in software, it’s easy to forget about the vulnerability of hardware. This means that even if the software is somehow trusted, the password must at some point reside in memory. The password must at some point be transmitted over a shared bus to the CPU. These provide vectors of attack to on-lookers in many forms. Of course, these attack vectors are far less likely than those presented by transmission and permanent storage, but they are no less severe (recent CPU vulnerabilities such as Spectre and Meltdown should serve as a stark reminder.)

The only way to fix this problem is to get rid of passwords altogether. There is hope! Research and private sector communities are working hard to do just that. New standards are emerging and growing mature. Unfortunately, passwords are so ubiquitous that it will take a long time to agree on and supplant passwords with new standards and technology.

At Cloudflare, we’ve been asking if there is something that can be done now, imminently. Today’s deep-dive into OPAQUE is one possible answer. OPAQUE is one among many examples of systems that enable a password to be useful without it ever leaving your possession. No one likes passwords, but as long they’re in use, at least we can ensure they are never given away.

I’ll be the first to admit that password-based authentication is annoying. Passwords are hard to remember, tedious to type, and notoriously insecure. Initiatives to reduce or replace passwords are promising. For example, WebAuthn is a standard for web authentication based primarily on public key cryptography using hardware (or software) tokens. Even so, passwords are frustratingly persistent as an authentication mechanism. Whether their persistence is due to their ease of implementation, familiarity to users, or simple ubiquity on the web and elsewhere, we’d like to make password-based authentication as secure as possible while they persist.

My internship at Cloudflare focused on OPAQUE, a cryptographic protocol that solves one of the most glaring security issues with password-based authentication on the web: though passwords are typically protected in transit by HTTPS, servers handle them in plaintext to check their correctness. Handling plaintext passwords is dangerous, as accidentally logging or caching them could lead to a catastrophic breach. The goal of the project, rather than to advocate for adoption of any particular protocol, is to show that OPAQUE is a viable option among many for authentication. Because the web case is most familiar to me, and likely many readers, I will use the web as my main example.

Web Authentication 101: Password-over-TLS

When you type in a password on the web, what happens? The website must check that the password you typed is the same as the one you originally registered with the site. But how does this check work?

Usually, your username and password are sent to a server. The server then checks if the registered password associated with your username matches the password you provided. Of course, to prevent an attacker eavesdropping on your Internet traffic from stealing your password, your connection to the server should be encrypted via HTTPS (HTTP-over-TLS).

Despite use of HTTPS, there still remains a glaring problem in this flow: the server must store a representation of your password somewhere. Servers are hard to secure, and breaches are all too common. Leaking this representation can cause catastrophic security problems. (For records of the latest breaches, check out https://haveibeenpwned.com/).

To make these leaks less devastating, servers often apply a hash function to user passwords. A hash function maps each password to a unique, random-looking value. It’s easy to apply the hash to a password, but almost impossible to reverse the function and retrieve the password. (That said, anyone can guess a password, apply the hash function, and check if the result is the same.)

With password hashing, plaintext passwords are no longer stored on servers.  An attacker who steals a password database no longer has direct access to passwords. Instead, the attacker must apply the hash to many possible passwords and compare the results with the leaked hashes.

Unfortunately, if a server hashes only the passwords, attackers can download precomputed rainbow tables containing hashes of trillions of possible passwords and almost instantly retrieve the plaintext passwords. (See https://project-rainbowcrack.com/table.htm for a list of some rainbow tables).

With this in mind, a good defense-in-depth strategy is to use salted hashing, where the server hashes your password appended to a random, per-user value called a salt. The server also saves the salt alongside the username, so the user never sees or needs to submit it. When the user submits a password, the server re-computes this hash function using the salt. An attacker who steals password data, i.e., the password representations and salt values, must then guess common passwords one by one and apply the (salted) hash function to each guessed password. Existing rainbow tables won’t help because they don’t take the salts into account, so the attacker needs to make a new rainbow table for each user!

This (hopefully) slows down the attack enough for the service to inform users of a breach, so they can change their passwords. In addition, the salted hashes should be hardened by applying a hash many times to further slow attacks. (See https://blog.cloudflare.com/keeping-passwords-safe-by-staying-up-to-date/ for a more detailed discussion).

These two mitigation strategies — encrypting the password in transit and storing salted, hardened hashes — are the current best practices.

A large security hole remains open. Password-over-TLS (as we will call it) requires users to send plaintext passwords to servers during login, because servers must see these passwords to match against registered passwords on file. Even a well-meaning server could accidentally cache or log your password attempt(s), or become corrupted in the course of checking passwords. (For example, Facebook detected in 2019 that it had accidentally been storing hundreds of millions of plaintext user passwords). Ideally, servers should never see a plaintext password at all.

But that’s quite a conundrum: how can you check a password if you never see the password? Enter OPAQUE: a Password-Authenticated Key Exchange (PAKE) protocol that simultaneously proves knowledge of a password and derives a secret key. Before describing OPAQUE in detail, we’ll first summarize PAKE functionalities in general.

Password Proofs with Password-Authenticated Key Exchange

Password-Authenticated Key Exchange (PAKE) was proposed by Bellovin and Merrit in 1992, with an initial motivation of allowing password-authentication without the possibility of dictionary attacks based on data transmitted over an insecure channel.

Essentially, a plain, or symmetric, PAKE is a cryptographic protocol that allows two parties who share only a password to establish a strong shared secret key. The goals of PAKE are:

1) The secret keys will match if the passwords match, and appear random otherwise.

2) Participants do not need to trust third parties (in particular, no Public Key Infrastructure),

3) The resulting secret key is not learned by anyone not participating in the protocol – including those who know the password.

4) The protocol does not reveal either parties’ password to each other (unless the passwords match), or to eavesdroppers.

In sum, the only way to successfully attack the protocol is to guess the password correctly while participating in the protocol. (Luckily, such attacks can be mostly thwarted by rate-limiting, i.e, blocking a user from logging in after a certain number of incorrect password attempts).

Given these requirements, password-over-TLS is clearly not a PAKE, because:

  • It relies on WebPKI, which places trust in third-parties called Certificate Authorities (see https://blog.cloudflare.com/introducing-certificate-transparency-and-nimbus/ for an in-depth explanation of WebPKI and some of its shortcomings).
  • The user’s password is revealed to the server.
  • Password-over-TLS provides the user no assurance that the server knows their password or a derivative of it — a server could accept any input from the user with no checks whatsoever.

That said, plain PAKE is still worse than Password-over-TLS, simply because it requires the server to store plaintext passwords. We need a PAKE that lets the server store salted hashes if we want to beat the current practice.

An improvement over plain PAKE is what’s called an asymmetric PAKE (aPAKE), because only the client knows the password, and the server knows a hashed password. An aPAKE has the four properties of PAKE, plus one more:

5) An attacker who steals password data stored on the server must perform a dictionary attack to retrieve the password.

The issue with most existing aPAKE protocols, however, is that they do not allow for a salted hash (or if they do, they require that salt to be transmitted to the user, which means the attacker has access to the salt beforehand and can begin computing a rainbow table for the user before stealing any data). We’d like, therefore, to upgrade the security property as follows:

5*) An attacker who steals password data stored on the server must perform a per-user dictionary attack to retrieve the password after the data is compromised.

OPAQUE is the first aPAKE protocol with a formal security proof that has this property: it allows for a completely secret salt.

OPAQUE – Servers safeguard secrets without knowing them!

OPAQUE: The Best Passwords Never Leave your Device

OPAQUE is what’s referred to as a strong aPAKE, which simply means that it resists these pre-computation attacks by using a secretly salted hash on the server. OPAQUE was proposed and formally analyzed by Stanislaw Jarecki, Hugo Krawcyzk and Jiayu Xu in 2018 (full disclosure: Stanislaw Jarecki is my academic advisor). The name OPAQUE is a combination of the names of two cryptographic protocols: OPRF and PAKE. We already know PAKE, but what is an OPRF? OPRF stands for Oblivious Pseudo-Random Function, which is a protocol by which two parties compute a function F(key, x) that is deterministic but outputs random-looking values. One party inputs the value x, and another party inputs the key – the party who inputs x learns the result F(key, x) but not the key, and the party providing the key learns nothing.  (You can dive into the math of OPRFs here: https://blog.cloudflare.com/privacy-pass-the-math/).

The core of OPAQUE is a method to store user secrets for safekeeping on a server, without giving the server access to those secrets. Instead of storing a traditional salted password hash, the server stores a secret envelope for you that is “locked” by two pieces of information: your password known only by you, and a random secret key (like a salt) known only by the server. To log in, the client initiates a cryptographic exchange that reveals the envelope key to the client, but, importantly, not to the server.

The server then sends the envelope to the user, who now can retrieve the encrypted keys. (The keys included in the envelope are a private-public key pair for the user, and a public key for the server.) These keys, once unlocked, will be the inputs to an Authenticated Key Exchange (AKE) protocol, which allows the user and server to establish a secret key which can be used to encrypt their future communication.

OPAQUE consists of two phases, being credential registration and login via key exchange.

OPAQUE: Registration Phase

Before registration, the user first signs up for a service and picks a username and password. Registration begins with the OPRF flow we just described: Alice (the user) and Bob (the server) do an OPRF exchange. The result is that Alice has a random key rwd, derived from the OPRF output F(key, pwd), where key is a server-owned OPRF key specific to Alice and pwd is Alice’s password.

Within his OPRF message, Bob sends the public key for his OPAQUE identity. Alice then generates a new private/public key pair, which will be her persistent OPAQUE identity for Bob’s service, and encrypts her private key along with Bob’s public key with the rwd (we will call the result an encrypted envelope). She sends this encrypted envelope along with her public key (unencrypted) to Bob, who stores the data she provided, along with Alice’s specific OPRF keysecret, in a database indexed by her username.

OPAQUE: The Best Passwords Never Leave your Device

OPAQUE: Login Phase

The login phase is very similar. It starts the same way as registration — with an OPRF flow. However, on the server side, instead of generating a new OPRF key, Bob instead looks up the one he created during Alice’s registration. He does this by looking up Alice’s username (which she provides in the first message), and retrieving his record of her. This record contains her public key, her encrypted envelope, and Bob’s OPRF key for Alice.

He also sends over the encrypted envelope which Alice can decrypt with the output of the OPRF flow. (If decryption fails, she aborts the protocol — this likely indicates that she typed her password incorrectly, or Bob isn’t who he says he is). If decryption succeeds, she now has her own secret key and Bob’s public key. She inputs these into an AKE protocol with Bob, who, in turn, inputs his private key and her public key, which gives them both a fresh shared secret key.

OPAQUE: The Best Passwords Never Leave your Device

Integrating OPAQUE with an AKE

An important question to ask here is: what AKE is suitable for OPAQUE? The emerging CFRG specification outlines several options, including 3DH and SIGMA-I. However, on the web, we already have an AKE at our disposal: TLS!

Recall that TLS is an AKE because it provides unilateral (and mutual) authentication with shared secret derivation. The core of TLS is a Diffie-Hellman key exchange, which by itself is unauthenticated, meaning that the parties running it have no way to verify who they are running it with. (This is a problem because when you log into your bank, or any other website that stores your private data, you want to be sure that they are who they say they are). Authentication primarily uses certificates, which are issued by trusted entities through a system called Public Key Infrastructure (PKI). Each certificate is associated with a secret key. To prove its identity, the server presents its certificate to the client, and signs the TLS handshake with its secret key.

Modifying this ubiquitous certificate-based authentication on the web is perhaps not the best place to start. Instead, an improvement would be to authenticate the TLS shared secret, using OPAQUE, after the TLS handshake completes. In other words, once a server is authenticated with its typical WebPKI certificate, clients could subsequently authenticate to the server. This authentication could take place “post handshake” in the TLS connection using OPAQUE.

Exported Authenticators are one mechanism for “post-handshake” authentication in TLS. They allow a server or client to provide proof of an identity without setting up a new TLS connection. Recall that in the standard web case, the server establishes their identity with a certificate (proving, for example, that they are “cloudflare.com”). But if the same server also holds alternate identities, they must run TLS again to prove who they are.

The basic Exported Authenticator flow works resembles a classical challenge-response protocol, and works as follows. (We’ll consider the server authentication case only, as the client case is symmetric).

OPAQUE: The Best Passwords Never Leave your Device

At any point after a TLS connection is established, Alice (the client) sends an authenticator request to indicate that she would like Bob (the server) to prove an additional identity. This request includes a context (an unpredictable string — think of this as a challenge), and extensions which include information about what identity the client wants to be provided. For example, the client could include the SNI extension to ask the server for a certificate associated with a certain domain name other than the one initially used in the TLS connection.

On receipt of the client message, if the server has a valid certificate corresponding to the request, it sends back an exported authenticator which proves that it has the secret key for the certificate. (This message has the same format as an Auth message from the client in TLS 1.3 handshake – it contains a Certificate, a CertificateVerify and a Finished message). If the server cannot or does not wish to authenticate with the requested certificate, it replies with an empty authenticator which contains only a well formed Finished message.

The client then checks that the Exported Authenticator it receives is well-formed, and then verifies that the certificate presented is valid, and if so, accepts the new identity.

In sum, Exported Authenticators provide authentication in a higher layer (such as the application layer) safely by leveraging the well-vetted cryptography and message formats of TLS. Furthermore, it is tied to the TLS session so that authentication messages can’t be copied and pasted from one TLS connection into another. In other words, Exported Authenticators provide exactly the right hooks needed to add OPAQUE-based authentication into TLS.

OPAQUE with Exported Authenticators (OPAQUE-EA)

OPAQUE: The Best Passwords Never Leave your Device

OPAQUE-EA allows OPAQUE to run at any point after a TLS connection has already been set up. Recall that Bob (the server) will store his OPAQUE identity, in this case a signing key and verification key, and Alice will store her identity — encrypted — on Bob’s server. (The registration flow where Alice stores her encrypted keys is the same as in regular OPAQUE, except she stores a signing key, so we will skip straight to the login flow). Alice and Bob run two request-authenticate EA flows, one for each party, and OPAQUE protocol messages ride along in the extensions section of the EAs. Let’s look in detail how this works.

First, Alice generates her OPRF message based on her password. She creates an Authenticator Request asking for Bob’s OPAQUE identity, and includes (in the extensions field) her username and her OPRF message, and sends this to Bob over their established TLS connection.

Bob receives the message and looks up Alice’s username in his database. He retrieves her OPAQUE record containing her verification key and encrypted envelope, and his OPRF key. He uses the OPRF key on the OPRF message, and creates an Exported Authenticator proving ownership of his OPAQUE signing key, with an extension containing his OPRF message and the encrypted envelope. Additionally, he sends a new Authenticator Request asking Alice to prove ownership of her OPAQUE signing key.

Alice parses the message and completes the OPRF evaluation using Bob’s message to get output rwd, and uses rwd to decrypt the envelope. This reveals her signing key and Bob’s public key. She uses Bob’s public key to validate his Authenticator Response proof, and, if it checks out, she creates and sends an Exported Authenticator proving that she holds the newly decrypted signing key. Bob checks the validity of her Exported Authenticator, and if it checks out, he accepts her login.

My project: OPAQUE-EA over HTTPS

Everything described above is supported by lots and lots of theory that has yet to find its way into practice. My project was to turn the theory into reality. I started with written descriptions of Exported Authenticators, OPAQUE, and a preliminary draft of OPAQUE-in-TLS. My goal was to get from those to a working prototype.

My demo shows the feasibility of implementing OPAQUE-EA on the web, completely removing plaintext passwords from the wire, even encrypted. This provides a possible alternative to the current password-over-TLS flow with better security properties, but no visible change to the user.

A few of the implementation details are worth knowing. In computer science, abstraction is a powerful tool. It means that we can often rely on existing tools and APIs to avoid duplication of effort. In my project I relied heavily on mint, an open-source implementation of TLS 1.3 in Go that is great for prototyping. I also used CIRCL’s OPRF API. I built libraries for Exported Authenticators, the core of OPAQUE, and OPAQUE-EA (which ties together the two).

I made the web demo by wrapping the OPAQUE-EA functionality in a simple HTTP server and client that pass messages to each other over HTTPS. Since a browser can’t run Go, I compiled from Go to WebAssembly (WASM) to get the Go functionality in the browser, and wrote a simple script in JavaScript to call the WASM functions needed.

Since current browsers do not give access to the underlying TLS connection on the client side, I had to implement a work-around to allow the client to access the exporter keys, namely, that the server simply computes the keys and sends them to the client over HTTPS. This workaround reduces the security of the resulting demo — it means that trust is placed in the server to provide the right keys. Even so, the user’s password is still safe, even if a malicious server provided bad keys— they just don’t have assurance that they actually previously registered with that server. However, in the future, browsers could include a mechanism to support exported keys and allow OPAQUE-EA to run with its full security properties.

You can explore my implementation on Github, and even follow the instructions to spin up your own OPAQUE-EA test server and client. I’d like to stress, however, that the implementation is meant as a proof-of-concept only, and must not be used for production systems without significant further review.

OPAQUE-EA Limitations

Despite its great properties, there will definitely be some hurdles in bringing OPAQUE-EA from a proof-of-concept to a fully fledged authentication mechanism.

Browser support for TLS exporter keys. As mentioned briefly before, to run OPAQUE-EA in a browser, you need to access secrets from the TLS connection called exporter keys. There is no way to do this in the current most popular browsers, so support for this functionality will need to be added.

Overhauling password databases. To adopt OPAQUE-EA, servers need not only to update their password-checking logic, but also completely overhaul their password databases. Because OPAQUE relies on special password representations that can only be generated interactively, existing salted hashed passwords cannot be automatically updated to OPAQUE records. Servers will likely need to run a special OPAQUE registration flow on a user-by-user basis. Because OPAQUE relies on buy-in from both the client and the server, servers may need to support the old method for a while before all clients catch up.

Reliance on emerging standards. OPAQUE-EA relies on OPRFs, which is in the process of standardization, and Exported Authenticators, a proposed standard. This means that support for these dependencies is not yet available in most existing cryptographic libraries, so early adopters may need to implement these tools themselves.

Summary

As long as people still use passwords, we’d like to make the process as secure as possible. Current methods rely on the risky practice of handling plaintext passwords on the server side while checking their correctness. PAKEs, and (specifically aPAKEs) allow secure password login without ever letting the server see the passwords.

OPAQUE is also being explored within other companies. According to Kevin Lewi, a research scientist from the Novi Research team at Facebook, they are “excited by the strong cryptographic guarantees provided by OPAQUE and are actively exploring OPAQUE as a method for further safeguarding credential-protected fields that are stored server-side.”

OPAQUE is one of the best aPAKEs out there, and can be fully integrated into TLS. You can check out the core OPAQUE implementation here and the demo TLS integration here. A running version of the demo is also available here. A Typescript client implementation of OPAQUE is coming soon. If you’re interested in implementing the protocol, or encounter any bugs with the current implementation, please drop us a line at [email protected]! Consider also subscribing to the IRTF CFRG mailing list to track discussion about the OPAQUE specification and its standardization.

Wallpaper that Crashes Android Phones

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2020/06/wallpaper_that_.html

This is interesting:

The image, a seemingly innocuous sunset (or dawn) sky above placid waters, may be viewed without harm. But if loaded as wallpaper, the phone will crash.

The fault does not appear to have been maliciously created. Rather, according to developers following Ice Universe’s Twitter thread, the problem lies in the way color space is handled by the Android OS.

The image was created using the RGB color space to display image hues, while Android 10 uses the sRGB color space protocol, according to 9to5Google contributor Dylan Roussel. When the Android phone cannot properly convert the Adobe RGB image, it crashes.

Security Vulnerabilities in the RCS Texting Protocol

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/12/security_vulner_21.html

Interesting research:

SRLabs founder Karsten Nohl, a researcher with a track record of exposing security flaws in telephony systems, argues that RCS is in many ways no better than SS7, the decades-old phone system carriers still used for calling and texting, which has long been known to be vulnerable to interception and spoofing attacks. While using end-to-end encrypted internet-based tools like iMessage and WhatsApp obviates many of those of SS7 issues, Nohl says that flawed implementations of RCS make it not much safer than the SMS system it hopes to replace.

Vulnerabilities in the WPA3 Wi-Fi Security Protocol

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2019/04/vulnerabilities_7.html

Researchers have found several vulnerabilities in the WPA3 Wi-Fi security protocol:

The design flaws we discovered can be divided in two categories. The first category consists of downgrade attacks against WPA3-capable devices, and the second category consists of weaknesses in the Dragonfly handshake of WPA3, which in the Wi-Fi standard is better known as the Simultaneous Authentication of Equals (SAE) handshake. The discovered flaws can be abused to recover the password of the Wi-Fi network, launch resource consumption attacks, and force devices into using weaker security groups. All attacks are against home networks (i.e. WPA3-Personal), where one password is shared among all users.

News article. Research paper: “Dragonblood: A Security Analysis of WPA3’s SAE Handshake“:

Abstract: The WPA3 certification aims to secure Wi-Fi networks, and provides several advantages over its predecessor WPA2, such as protection against offline dictionary attacks and forward secrecy. Unfortunately, we show that WPA3 is affected by several design flaws,and analyze these flaws both theoretically and practically. Most prominently, we show that WPA3’s Simultaneous Authentication of Equals (SAE) handshake, commonly known as Dragonfly, is affected by password partitioning attacks. These attacks resemble dictionary attacks and allow an adversary to recover the password by abusing timing or cache-based side-channel leaks. Our side-channel attacks target the protocol’s password encoding method. For instance, our cache-based attack exploits SAE’s hash-to-curve algorithm. The resulting attacks are efficient and low cost: brute-forcing all 8-character lowercase password requires less than 125$in Amazon EC2 instances. In light of ongoing standardization efforts on hash-to-curve, Password-Authenticated Key Exchanges (PAKEs), and Dragonfly as a TLS handshake, our findings are also of more general interest. Finally, we discuss how to mitigate our attacks in a backwards-compatible manner, and explain how minor changes to the protocol could have prevented most of our attack

Monitoring your Amazon SNS message filtering activity with Amazon CloudWatch

Post Syndicated from Rachel Richardson original https://aws.amazon.com/blogs/compute/monitoring-your-amazon-sns-message-filtering-activity-with-amazon-cloudwatch/

This post is courtesy of Otavio Ferreira, Manager, Amazon SNS, AWS Messaging.

Amazon SNS message filtering provides a set of string and numeric matching operators that allow each subscription to receive only the messages of interest. Hence, SNS message filtering can simplify your pub/sub messaging architecture by offloading the message filtering logic from your subscriber systems, as well as the message routing logic from your publisher systems.

After you set the subscription attribute that defines a filter policy, the subscribing endpoint receives only the messages that carry attributes matching this filter policy. Other messages published to the topic are filtered out for this subscription. In this way, the native integration between SNS and Amazon CloudWatch provides visibility into the number of messages delivered, as well as the number of messages filtered out.

CloudWatch metrics are captured automatically for you. To get started with SNS message filtering, see Filtering Messages with Amazon SNS.

Message Filtering Metrics

The following six CloudWatch metrics are relevant to understanding your SNS message filtering activity:

  • NumberOfMessagesPublished – Inbound traffic to SNS. This metric tracks all the messages that have been published to the topic.
  • NumberOfNotificationsDelivered – Outbound traffic from SNS. This metric tracks all the messages that have been successfully delivered to endpoints subscribed to the topic. A delivery takes place either when the incoming message attributes match a subscription filter policy, or when the subscription has no filter policy at all, which results in a catch-all behavior.
  • NumberOfNotificationsFilteredOut – This metric tracks all the messages that were filtered out because they carried attributes that didn’t match the subscription filter policy.
  • NumberOfNotificationsFilteredOut-NoMessageAttributes – This metric tracks all the messages that were filtered out because they didn’t carry any attributes at all and, consequently, didn’t match the subscription filter policy.
  • NumberOfNotificationsFilteredOut-InvalidAttributes – This metric keeps track of messages that were filtered out because they carried invalid or malformed attributes and, thus, didn’t match the subscription filter policy.
  • NumberOfNotificationsFailed – This last metric tracks all the messages that failed to be delivered to subscribing endpoints, regardless of whether a filter policy had been set for the endpoint. This metric is emitted after the message delivery retry policy is exhausted, and SNS stops attempting to deliver the message. At that moment, the subscribing endpoint is likely no longer reachable. For example, the subscribing SQS queue or Lambda function has been deleted by its owner. You may want to closely monitor this metric to address message delivery issues quickly.

Message filtering graphs

Through the AWS Management Console, you can compose graphs to display your SNS message filtering activity. The graph shows the number of messages published, delivered, and filtered out within the timeframe you specify (1h, 3h, 12h, 1d, 3d, 1w, or custom).

SNS message filtering for CloudWatch Metrics

To compose an SNS message filtering graph with CloudWatch:

  1. Open the CloudWatch console.
  2. Choose Metrics, SNS, All Metrics, and Topic Metrics.
  3. Select all metrics to add to the graph, such as:
    • NumberOfMessagesPublished
    • NumberOfNotificationsDelivered
    • NumberOfNotificationsFilteredOut
  4. Choose Graphed metrics.
  5. In the Statistic column, switch from Average to Sum.
  6. Title your graph with a descriptive name, such as “SNS Message Filtering”

After you have your graph set up, you may want to copy the graph link for bookmarking, emailing, or sharing with co-workers. You may also want to add your graph to a CloudWatch dashboard for easy access in the future. Both actions are available to you on the Actions menu, which is found above the graph.

Summary

SNS message filtering defines how SNS topics behave in terms of message delivery. By using CloudWatch metrics, you gain visibility into the number of messages published, delivered, and filtered out. This enables you to validate the operation of filter policies and more easily troubleshoot during development phases.

SNS message filtering can be implemented easily with existing AWS SDKs by applying message and subscription attributes across all SNS supported protocols (Amazon SQS, AWS Lambda, HTTP, SMS, email, and mobile push). CloudWatch metrics for SNS message filtering is available now, in all AWS Regions.

For information about pricing, see the CloudWatch pricing page.

For more information, see:

Getting Rid of Your Mac? Here’s How to Securely Erase a Hard Drive or SSD

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/how-to-wipe-a-mac-hard-drive/

erasing a hard drive and a solid state drive

What do I do with a Mac that still has personal data on it? Do I take out the disk drive and smash it? Do I sweep it with a really strong magnet? Is there a difference in how I handle a hard drive (HDD) versus a solid-state drive (SSD)? Well, taking a sledgehammer or projectile weapon to your old machine is certainly one way to make the data irretrievable, and it can be enormously cathartic as long as you follow appropriate safety and disposal protocols. But there are far less destructive ways to make sure your data is gone for good. Let me introduce you to secure erasing.

Which Type of Drive Do You Have?

Before we start, you need to know whether you have a HDD or a SSD. To find out, or at least to make sure, you click on the Apple menu and select “About this Mac.” Once there, select the “Storage” tab to see which type of drive is in your system.

The first example, below, shows a SATA Disk (HDD) in the system.

SATA HDD

In the next case, we see we have a Solid State SATA Drive (SSD), plus a Mac SuperDrive.

Mac storage dialog showing SSD

The third screen shot shows an SSD, as well. In this case it’s called “Flash Storage.”

Flash Storage

Make Sure You Have a Backup

Before you get started, you’ll want to make sure that any important data on your hard drive has moved somewhere else. OS X’s built-in Time Machine backup software is a good start, especially when paired with Backblaze. You can learn more about using Time Machine in our Mac Backup Guide.

With a local backup copy in hand and secure cloud storage, you know your data is always safe no matter what happens.

Once you’ve verified your data is backed up, roll up your sleeves and get to work. The key is OS X Recovery — a special part of the Mac operating system since OS X 10.7 “Lion.”

How to Wipe a Mac Hard Disk Drive (HDD)

NOTE: If you’re interested in wiping an SSD, see below.

    1. Make sure your Mac is turned off.
    2. Press the power button.
    3. Immediately hold down the command and R keys.
    4. Wait until the Apple logo appears.
    5. Select “Disk Utility” from the OS X Utilities list. Click Continue.
    6. Select the disk you’d like to erase by clicking on it in the sidebar.
    7. Click the Erase button.
    8. Click the Security Options button.
    9. The Security Options window includes a slider that enables you to determine how thoroughly you want to erase your hard drive.

There are four notches to that Security Options slider. “Fastest” is quick but insecure — data could potentially be rebuilt using a file recovery app. Moving that slider to the right introduces progressively more secure erasing. Disk Utility’s most secure level erases the information used to access the files on your disk, then writes zeroes across the disk surface seven times to help remove any trace of what was there. This setting conforms to the DoD 5220.22-M specification.

  1. Once you’ve selected the level of secure erasing you’re comfortable with, click the OK button.
  2. Click the Erase button to begin. Bear in mind that the more secure method you select, the longer it will take. The most secure methods can add hours to the process.

Once it’s done, the Mac’s hard drive will be clean as a whistle and ready for its next adventure: a fresh installation of OS X, being donated to a relative or a local charity, or just sent to an e-waste facility. Of course you can still drill a hole in your disk or smash it with a sledgehammer if it makes you happy, but now you know how to wipe the data from your old computer with much less ruckus.

The above instructions apply to older Macintoshes with HDDs. What do you do if you have an SSD?

Securely Erasing SSDs, and Why Not To

Most new Macs ship with solid state drives (SSDs). Only the iMac and Mac mini ship with regular hard drives anymore, and even those are available in pure SSD variants if you want.

If your Mac comes equipped with an SSD, Apple’s Disk Utility software won’t actually let you zero the hard drive.

Wait, what?

In a tech note posted to Apple’s own online knowledgebase, Apple explains that you don’t need to securely erase your Mac’s SSD:

With an SSD drive, Secure Erase and Erasing Free Space are not available in Disk Utility. These options are not needed for an SSD drive because a standard erase makes it difficult to recover data from an SSD.

In fact, some folks will tell you not to zero out the data on an SSD, since it can cause wear and tear on the memory cells that, over time, can affect its reliability. I don’t think that’s nearly as big an issue as it used to be — SSD reliability and longevity has improved.

If “Standard Erase” doesn’t quite make you feel comfortable that your data can’t be recovered, there are a couple of options.

FileVault Keeps Your Data Safe

One way to make sure that your SSD’s data remains secure is to use FileVault. FileVault is whole-disk encryption for the Mac. With FileVault engaged, you need a password to access the information on your hard drive. Without it, that data is encrypted.

There’s one potential downside of FileVault — if you lose your password or the encryption key, you’re screwed: You’re not getting your data back any time soon. Based on my experience working at a Mac repair shop, losing a FileVault key happens more frequently than it should.

When you first set up a new Mac, you’re given the option of turning FileVault on. If you don’t do it then, you can turn on FileVault at any time by clicking on your Mac’s System Preferences, clicking on Security & Privacy, and clicking on the FileVault tab. Be warned, however, that the initial encryption process can take hours, as will decryption if you ever need to turn FileVault off.

With FileVault turned on, you can restart your Mac into its Recovery System (by restarting the Mac while holding down the command and R keys) and erase the hard drive using Disk Utility, once you’ve unlocked it (by selecting the disk, clicking the File menu, and clicking Unlock). That deletes the FileVault key, which means any data on the drive is useless.

FileVault doesn’t impact the performance of most modern Macs, though I’d suggest only using it if your Mac has an SSD, not a conventional hard disk drive.

Securely Erasing Free Space on Your SSD

If you don’t want to take Apple’s word for it, if you’re not using FileVault, or if you just want to, there is a way to securely erase free space on your SSD. It’s a little more involved but it works.

Before we get into the nitty-gritty, let me state for the record that this really isn’t necessary to do, which is why Apple’s made it so hard to do. But if you’re set on it, you’ll need to use Apple’s Terminal app. Terminal provides you with command line interface access to the OS X operating system. Terminal lives in the Utilities folder, but you can access Terminal from the Mac’s Recovery System, as well. Once your Mac has booted into the Recovery partition, click the Utilities menu and select Terminal to launch it.

From a Terminal command line, type:

diskutil secureErase freespace VALUE /Volumes/DRIVE

That tells your Mac to securely erase the free space on your SSD. You’ll need to change VALUE to a number between 0 and 4. 0 is a single-pass run of zeroes; 1 is a single-pass run of random numbers; 2 is a 7-pass erase; 3 is a 35-pass erase; and 4 is a 3-pass erase. DRIVE should be changed to the name of your hard drive. To run a 7-pass erase of your SSD drive in “JohnB-Macbook”, you would enter the following:

diskutil secureErase freespace 2 /Volumes/JohnB-Macbook

And remember, if you used a space in the name of your Mac’s hard drive, you need to insert a leading backslash before the space. For example, to run a 35-pass erase on a hard drive called “Macintosh HD” you enter the following:

diskutil secureErase freespace 3 /Volumes/Macintosh\ HD

Something to remember is that the more extensive the erase procedure, the longer it will take.

When Erasing is Not Enough — How to Destroy a Drive

If you absolutely, positively need to be sure that all the data on a drive is irretrievable, see this Scientific American article (with contributions by Gleb Budman, Backblaze CEO), How to Destroy a Hard Drive — Permanently.

The post Getting Rid of Your Mac? Here’s How to Securely Erase a Hard Drive or SSD appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.

Critical PGP Vulnerability

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/05/critical_pgp_vu.html

EFF is reporting that a critical vulnerability has been discovered in PGP and S/MIME. No details have been published yet, but one of the researchers wrote:

We’ll publish critical vulnerabilities in PGP/GPG and S/MIME email encryption on 2018-05-15 07:00 UTC. They might reveal the plaintext of encrypted emails, including encrypted emails sent in the past. There are currently no reliable fixes for the vulnerability. If you use PGP/GPG or S/MIME for very sensitive communication, you should disable it in your email client for now.

This sounds like a protocol vulnerability, but we’ll learn more tomorrow.

News articles.

Announcing the new AWS Certified Security – Specialty exam

Post Syndicated from Janna Pellegrino original https://aws.amazon.com/blogs/architecture/announcing-the-new-aws-certified-security-specialty-exam/

Good news for cloud security experts: following our most popular beta exam ever, the AWS Certified Security – Specialty exam is here. This new exam allows experienced cloud security professionals to demonstrate and validate their knowledge of how to secure the AWS platform.

About the exam
The security exam covers incident response, logging and monitoring, infrastructure security, identity and access management, and data protection. The exam is open to anyone who currently holds a Cloud Practitioner or Associate-level certification. We recommend candidates have five years of IT security experience designing and implementing security solutions, and at least two years of hands-on experience securing AWS workloads.

The exam validates:

  • An understanding of specialized data classifications and AWS data protection mechanisms.
  • An understanding of data encryption methods and AWS mechanisms to implement them.
  • An understanding of secure Internet protocols and AWS mechanisms to implement them.
  • A working knowledge of AWS security services and features of services to provide a secure production environment.
  • Competency gained from two or more years of production deployment experience using AWS security services and features.
  • Ability to make trade-off decisions with regard to cost, security, and deployment complexity given a set of application requirements.
  • An understanding of security operations and risk.

Learn more and register >>

How to prepare
We have training and other resources to help you prepare for the exam:

AWS Training (aws.amazon.com/training)

Additional Resources

Learn more and register >>

Please contact us if you have questions about exam registration.

Good luck!

Announcing the new AWS Certified Security – Specialty exam

Post Syndicated from Ozlem Yilmaz original https://aws.amazon.com/blogs/security/announcing-the-new-aws-certified-security-specialty-exam/

Good news for cloud security experts: the AWS Certified Security — Specialty exam is here. This new exam allows experienced cloud security professionals to demonstrate and validate their knowledge of how to secure the AWS platform.

About the exam

The security exam covers incident response, logging and monitoring, infrastructure security, identity and access management, and data protection. The exam is open to anyone who currently holds a Cloud Practitioner or Associate-level certification. We recommend candidates have five years of IT security experience designing and implementing security solutions, and at least two years of hands-on experience securing AWS workloads.

The exam validates your understanding of:

  • Specialized data classifications and AWS data protection mechanisms
  • Data encryption methods and AWS mechanisms to implement them
  • Secure Internet protocols and AWS mechanisms to implement them
  • AWS security services and features of services to provide a secure production environment
  • Making tradeoff decisions with regard to cost, security, and deployment complexity given a set of application requirements
  • Security operations and risk

How to prepare

We have training and other resources to help you prepare for the exam.

AWS Training that includes:

Additional Resources

Learn more and register here, and please contact us if you have questions about exam registration.

Want more AWS Security news? Follow us on Twitter.

Subverting Backdoored Encryption

Post Syndicated from Bruce Schneier original https://www.schneier.com/blog/archives/2018/04/subverting_back.html

This is a really interesting research result. This paper proves that two parties can create a secure communications channel using a communications system with a backdoor. It’s a theoretical result, so it doesn’t talk about how easy that channel is to create. And the assumptions on the adversary are pretty reasonable: that each party can create his own randomness, and that the government isn’t literally eavesdropping on every single part of the network at all times.

This result reminds me a lot of the work about subliminal channels from the 1980s and 1990s, and the notions of how to build an anonymous communications system on top of an identified system. Basically, it’s always possible to overlay a system around and outside any closed system.

How to Subvert Backdoored Encryption: Security Against Adversaries that Decrypt All Ciphertexts,” by Thibaut Horel and Sunoo Park and Silas Richelson and Vinod Vaikuntanathan.

Abstract: In this work, we examine the feasibility of secure and undetectable point-to-point communication in a world where governments can read all the encrypted communications of their citizens. We consider a world where the only permitted method of communication is via a government-mandated encryption scheme, instantiated with government-mandated keys. Parties cannot simply encrypt ciphertexts of some other encryption scheme, because citizens caught trying to communicate outside the government’s knowledge (e.g., by encrypting strings which do not appear to be natural language plaintexts) will be arrested. The one guarantee we suppose is that the government mandates an encryption scheme which is semantically secure against outsiders: a perhaps reasonable supposition when a government might consider it advantageous to secure its people’s communication against foreign entities. But then, what good is semantic security against an adversary that holds all the keys and has the power to decrypt?

We show that even in the pessimistic scenario described, citizens can communicate securely and undetectably. In our terminology, this translates to a positive statement: all semantically secure encryption schemes support subliminal communication. Informally, this means that there is a two-party protocol between Alice and Bob where the parties exchange ciphertexts of what appears to be a normal conversation even to someone who knows the secret keys and thus can read the corresponding plaintexts. And yet, at the end of the protocol, Alice will have transmitted her secret message to Bob. Our security definition requires that the adversary not be able to tell whether Alice and Bob are just having a normal conversation using the mandated encryption scheme, or they are using the mandated encryption scheme for subliminal communication.

Our topics may be thought to fall broadly within the realm of steganography: the science of hiding secret communication within innocent-looking messages, or cover objects. However, we deal with the non-standard setting of an adversarially chosen distribution of cover objects (i.e., a stronger-than-usual adversary), and we take advantage of the fact that our cover objects are ciphertexts of a semantically secure encryption scheme to bypass impossibility results which we show for broader classes of steganographic schemes. We give several constructions of subliminal communication schemes under the assumption that key exchange protocols with pseudorandom messages exist (such as Diffie-Hellman, which in fact has truly random messages). Each construction leverages the assumed semantic security of the adversarially chosen encryption scheme, in order to achieve subliminal communication.

Tag Amazon EBS Snapshots on Creation and Implement Stronger Security Policies

Post Syndicated from Woo Kim original https://aws.amazon.com/blogs/compute/tag-amazon-ebs-snapshots-on-creation-and-implement-stronger-security-policies/

This blog was contributed by Rucha Nene, Sr. Product Manager for Amazon EBS

AWS customers use tags to track ownership of resources, implement compliance protocols, control access to resources via IAM policies, and drive their cost accounting processes. Last year, we made tagging for Amazon EC2 instances and Amazon EBS volumes easier by adding the ability to tag these resources upon creation. We are now extending this capability to EBS snapshots.

Earlier, you could tag your EBS snapshots only after the resource had been created and sometimes, ended up with EBS snapshots in an untagged state if tagging failed. You also could not control the actions that users and groups could take over specific snapshots, or enforce tighter security policies.

To address these issues, we are making tagging for EBS snapshots more flexible and giving customers more control over EBS snapshots by introducing two new capabilities:

  • Tag on creation for EBS snapshots – You can now specify tags for EBS snapshots as part of the API call that creates the resource or via the Amazon EC2 Console when creating an EBS snapshot.
  • Resource-level permission and enforced tag usage – The CreateSnapshot, DeleteSnapshot, and ModifySnapshotAttrribute API actions now support IAM resource-level permissions. You can now write IAM policies that mandate the use of specific tags when taking actions on EBS snapshots.

Tag on creation

You can now specify tags for EBS snapshots as part of the API call that creates the resources. The resource creation and the tagging are performed atomically; both must succeed in order for the operation CreateSnapshot to succeed. You no longer need to build tagging scripts that run after EBS snapshots have been created.

Here’s how you specify tags when you create an EBS snapshot, using the console:

  1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
  2. In the navigation pane, choose Snapshots, Create Snapshot.
  3. On the Create Snapshot page, select the volume for which to create a snapshot.
  4. (Optional) Choose Add tags to your snapshot. For each tag, provide a tag key and a tag value.
  5. Choose Create Snapshot.

Using the AWS CLI:

aws ec2 create-snapshot --volume-id vol-0c0e757e277111f3c --description 'Prod_Backup' --tag-specifications 
'ResourceType=snapshot,Tags=[{Key=costcenter,Value=115},{Key=IsProd,Value=Yes}]'

To learn more, see Using Tags.

Resource-level permissions and enforced tag usage

CreateSnapshot, DeleteSnapshot, and ModifySnapshotAttribute now support resource-level permissions, which allow you to exercise more control over EBS snapshots. You can write IAM policies that give you precise control over access to resources and let you specify which users are able to create snapshots for a given set of volumes. You can also enforce the use of specific tags to help track resources and achieve more accurate cost allocation reporting.

For example, here’s a statement that requires that the costcenter tag (with a value of “115”) be present on the volume from which snapshots are being created. It requires that this tag be applied to all newly created snapshots. In addition, it requires that the created snapshots are tagged with User:username for the customer.

{
   "Version":"2012-10-17",
   "Statement":[
      {
         "Effect":"Allow",
         "Action":"ec2:CreateSnapshot",
         "Resource":"arn:aws:ec2:us-east-1:123456789012:volume/*",
	   "Condition": {
		"StringEquals":{
               "ec2:ResourceTag/costcenter":"115"
}
 }
	
      },
      {
         "Sid":"AllowCreateTaggedSnapshots",
         "Effect":"Allow",
         "Action":"ec2:CreateSnapshot",
         "Resource":"arn:aws:ec2:us-east-1::snapshot/*",
         "Condition":{
            "StringEquals":{
               "aws:RequestTag/costcenter":"115",
		   "aws:RequestTag/User":"${aws:username}"
            },
            "ForAllValues:StringEquals":{
               "aws:TagKeys":[
                  "costcenter",
			"User"
               ]
            }
         }
      },
      {
         "Effect":"Allow",
         "Action":"ec2:CreateTags",
         "Resource":"arn:aws:ec2:us-east-1::snapshot/*",
         "Condition":{
            "StringEquals":{
               "ec2:CreateAction":"CreateSnapshot"
            }
         }
      }
   ]
}

To implement stronger compliance and security policies, you could also restrict access to DeleteSnapshot, if the resource is not tagged with the user’s name. Here’s a statement that allows the deletion of a snapshot only if the snapshot is tagged with User:username for the customer.

{
   "Version":"2012-10-17",
   "Statement":[
      {
         "Effect":"Allow",
         "Action":"ec2:DeleteSnapshot",
         "Resource":"arn:aws:ec2:us-east-1::snapshot/*",
         "Condition":{
            "StringEquals":{
               "ec2:ResourceTag/User":"${aws:username}"
            }
         }
      }
   ]
}

To learn more and to see some sample policies, see IAM Policies for Amazon EC2 and Working with Snapshots.

Available Now

These new features are available now in all AWS Regions. You can start using it today from the Amazon EC2 Console, AWS Command Line Interface (CLI), or the AWS APIs.

Leveraging AWS Marketplace Partner Storage Solutions for Microsoft

Post Syndicated from islawson original https://aws.amazon.com/blogs/architecture/leveraging-aws-marketplace-partner-storage-solutions-for-microsoft/

Designing a cloud storage solution to accommodate traditional enterprise software such as Microsoft SharePoint can be challenging. Microsoft SharePoint is complex and demands a lot of the underlying storage that’s used for its many databases and content repositories. To ensure that the selected storage platform can accommodate the availability, connectivity, and performance requirements recommended by Microsoft you need to use third-party storage solutions that build on and extend the functionality and performance of AWS storage services.

An appropriate storage solution for Microsoft SharePoint needs to provide data redundancy, high availability, fault tolerance, strong encryption, standard connectivity protocols, point-in-time data recovery, compression, ease of management, directory integration, and support.

AWS Marketplace is uniquely positioned as a procurement channel to find a third-party storage product that provides the additional technology layered on top of AWS storage services. The third-party storage products are provided and maintained by industry newcomers with born-in-the-cloud solutions as well as existing industry leaders. They include many mainstream storage products that are already familiar and commonly deployed in enterprises.

We recently released the “Leveraging AWS Marketplace Storage Solutions for Microsoft SharePoint” whitepaper to walk through the deployment and configuration of SoftNAS Cloud NAS, an AWS Marketplace third-party storage product that provides secure, highly available, redundant, and fault-tolerant storage to the Microsoft SharePoint collaboration suite.

About the Author

Israel Lawson is a senior solutions architect on the AWS Marketplace team.

Tracking Cookies and GDPR

Post Syndicated from Bozho original https://techblog.bozho.net/tracking-cookies-gdpr/

GDPR is the new data protection regulation, as you probably already know. I’ve given a detailed practical advice for what it means for developers (and product owners). However, there’s one thing missing there – cookies. The elephant in the room.

Previously I’ve stated that cookies are subject to another piece of legislation – the ePrivacy directive, which is getting updated and its new version will be in force a few years from now. And while that’s technically correct, cookies seem to be affected by GDPR as well. In a way I’ve underestimated that effect.

When you do a Google search on “GDPR cookies”, you’ll pretty quickly realize that a) there’s not too much information and b) there’s not much technical understanding of the issue.

What appears to be the consensus is that GDPR does change the way cookies are handled. More specifically – tracking cookies. Here’s recital 30:

(30) Natural persons may be associated with online identifiers provided by their devices, applications, tools and protocols, such as internet protocol addresses, cookie identifiers or other identifiers such as radio frequency identification tags. This may leave traces which, in particular when combined with unique identifiers and other information received by the servers, may be used to create profiles of the natural persons and identify them.

How tracking cookies work – a 3rd party (usually an ad network) gives you a code snippet that you place on your website, for example to display ads. That code snippet, however, calls “home” (makes a request to the 3rd party domain). If the 3rd party has previously been used on your computer, it has created a cookie. In the example of Facebook, they have the cookie with your Facebook identifier because you’ve logged in to Facebook. So this cookie (with your identifier) is sent with the request. The request also contains all the details from the page. In effect, you are uniquely identified by an identifier (in the case of Facebook and Google – fully identified, rather than some random anonymous identifier as with other ad networks).

Your behaviour on the website is personal data. It gets associated with your identifier, which in turn is associated with your profile. And all of that is personal data. Who is responsible for collecting the website behaviour data, i.e. who is the “controller”? Is it Facebook (or any other 3rd party) that technically does the collection? No, it’s the website owner, as the behaviour data is obtained on their website, and they have put the tracking piece of code there. So they bear responsibility.

What’s the responsibility? So far it boiled down to displaying the useless “we use cookies” warning that nobody cares about. And the current (old) ePrivacy directive and its interpretations says that this is enough – if the users actions can unambiguously mean that they are fine with cookies – i.e. if they continue to use the website after seeing the warning – then you’re fine. This is no longer true from a GDPR perspective – you are collecting user data and you have to have a lawful ground for processing.

For the data collected by tracking cookies you have two options – “consent” and “legitimate interest”. Legitimate interest will be hard to prove – it is not something that a user reasonably expects, it is not necessary for you to provide the service. If your lawyers can get that option to fly, good for them, but I’m not convinced regulators will be happy with that.

The other option is “consent”. You have to ask your users explicitly – that means “with a checkbox” – to let you use tracking cookies. That has two serious implications – from technical and usability point of view.

  • The technical issue is that the data is sent via 3rd party code as soon as the page loads and before the user can give their consent. And that’s already a violation. You can, of course, have the 3rd party code be dynamically inserted only after the user gives consent, but that will require some fiddling with javascript and might not always work depending on the provider. And you’d have to support opt-out at any time (which would in turn disable the 3rd party snippet). It would require actual coding, rather than just copy-pasting a snippet.
  • The usability aspect is the bigger issue – while you could neatly tuck a cookie warning at the bottom, you’d now have to have a serious, “stop the world” popup that asks for consent if you want anyone to click it. You can, of course, just add a checkbox to the existing cookie warning, but don’t expect anyone to click it.

These aspects pose a significant questions: is it worth it to have tracking cookies? Is developing new functionality worth it, is interrupting the user worth it, and is implementing new functionality just so that users never clicks a hidden checkbox worth it? Especially given that Firefox now blocks all tracking cookies and possibly other browsers will follow?

That by itself is an interesting topic – Firefox has basically implemented the most strict form of requirements of the upcoming ePrivacy directive update (that would turn it into an ePrivacy regulation). Other browsers will have to follow, even though Google may not be happy to block their own tracking cookies. I hope other browsers follow Firefox in tracking protection and the issue will be gone automatically.

To me it seems that it will be increasingly not worthy to have tracking cookies on your website. They add regulatory obligations for you and give you very little benefit (yes, you could track engagement from ads, but you can do that in other ways, arguably by less additional code than supporting the cookie consents). And yes, the cookie consent will be “outsourced” to browsers after the ePrivacy regulation is passed, but we can’t be sure at the moment whether there won’t be technical whack-a-mole between browsers and advertisers and whether you wouldn’t still need additional effort to have dynamic consent for tracking cookies. (For example there are reported issues that Firefox used to make Facebook login fail if tracking protection is enabled. Which could be a simple bug, or could become a strategy by big vendors in the future to force browsers into a less strict tracking protection).

Okay, we’ve decided it’s not worth it managing tracking cookies. But do you have a choice as a website owner? Can you stop your ad network from using them? (Remember – you are liable if users’ data is collected by visiting your website). And currently the answer is no – you can’t disable that. You can’t have “just the ads”. This is part of the “deal” – you get money for the ads you place, but you participate in a big “surveillance” network. Users have a way to opt out (e.g. Google AdWords gives them that option). You, as a website owner, don’t.

Facebook has a recommendations page that says “you take care of getting the consent”. But for example the “like button” plugin doesn’t have an option to not send any data to Facebook.

And sometimes you don’t want to serve ads, just track user behaviour and measure conversion. But even if you ask for consent for that and conditionally insert the plugin/snippet, do you actually know what data it sends? And what it’s used for? Because you have to know in order to inform your users. “Do you agree to use tracking cookies that Facebook has inserted in order to collect data about your behaviour on our website” doesn’t sound compelling.

So, what to do? The easiest thing is just not to use any 3rd party ad-related plugins. But that’s obviously not an option, as ad revenue is important, especially in the publishing industry. I don’t have a good answer, apart from “Regulators should pressure ad networks to provide opt-outs and clearly document their data usage”. They have to do that under GDPR, and while website owners are responsible for their users’ data, the ad networks that are in the role of processors in this case (as you delegate the data collection for your visitors to them) also have obligation to assist you in fulfilling your obligations. So ask Facebook – what should I do with your tracking cookies? And when the regulator comes after a privacy-aware customer files a complaint, you could prove that you’ve tried.

The ethical debate whether it’s wrong to collect data about peoples’ behaviour without their informed consent is an easy one. And that’s why I don’t put blame on the regulators – they are putting the ethical consensus in law. It gets more complicated if not allowing tracking means some internet services are no longer profitable and therefore can’t exist. Can we have the cake and eat it too?

The post Tracking Cookies and GDPR appeared first on Bozho's tech blog.

Message Filtering Operators for Numeric Matching, Prefix Matching, and Blacklisting in Amazon SNS

Post Syndicated from Christie Gifrin original https://aws.amazon.com/blogs/compute/message-filtering-operators-for-numeric-matching-prefix-matching-and-blacklisting-in-amazon-sns/

This blog was contributed by Otavio Ferreira, Software Development Manager for Amazon SNS

Message filtering simplifies the overall pub/sub messaging architecture by offloading message filtering logic from subscribers, as well as message routing logic from publishers. The initial launch of message filtering provided a basic operator that was based on exact string comparison. For more information, see Simplify Your Pub/Sub Messaging with Amazon SNS Message Filtering.

Today, AWS is announcing an additional set of filtering operators that bring even more power and flexibility to your pub/sub messaging use cases.

Message filtering operators

Amazon SNS now supports both numeric and string matching. Specifically, string matching operators allow for exact, prefix, and “anything-but” comparisons, while numeric matching operators allow for exact and range comparisons, as outlined below. Numeric matching operators work for values between -10e9 and +10e9 inclusive, with five digits of accuracy right of the decimal point.

  • Exact matching on string values (Whitelisting): Subscription filter policy   {"sport": ["rugby"]} matches message attribute {"sport": "rugby"} only.
  • Anything-but matching on string values (Blacklisting): Subscription filter policy {"sport": [{"anything-but": "rugby"}]} matches message attributes such as {"sport": "baseball"} and {"sport": "basketball"} and {"sport": "football"} but not {"sport": "rugby"}
  • Prefix matching on string values: Subscription filter policy {"sport": [{"prefix": "bas"}]} matches message attributes such as {"sport": "baseball"} and {"sport": "basketball"}
  • Exact matching on numeric values: Subscription filter policy {"balance": [{"numeric": ["=", 301.5]}]} matches message attributes {"balance": 301.500} and {"balance": 3.015e2}
  • Range matching on numeric values: Subscription filter policy {"balance": [{"numeric": ["<", 0]}]} matches negative numbers only, and {"balance": [{"numeric": [">", 0, "<=", 150]}]} matches any positive number up to 150.

As usual, you may apply the “AND” logic by appending multiple keys in the subscription filter policy, and the “OR” logic by appending multiple values for the same key, as follows:

  • AND logic: Subscription filter policy {"sport": ["rugby"], "language": ["English"]} matches only messages that carry both attributes {"sport": "rugby"} and {"language": "English"}
  • OR logic: Subscription filter policy {"sport": ["rugby", "football"]} matches messages that carry either the attribute {"sport": "rugby"} or {"sport": "football"}

Message filtering operators in action

Here’s how this new set of filtering operators works. The following example is based on a pharmaceutical company that develops, produces, and markets a variety of prescription drugs, with research labs located in Asia Pacific and Europe. The company built an internal procurement system to manage the purchasing of lab supplies (for example, chemicals and utensils), office supplies (for example, paper, folders, and markers) and tech supplies (for example, laptops, monitors, and printers) from global suppliers.

This distributed system is composed of the four following subsystems:

  • A requisition system that presents the catalog of products from suppliers, and takes orders from buyers
  • An approval system for orders targeted to Asia Pacific labs
  • Another approval system for orders targeted to European labs
  • A fulfillment system that integrates with shipping partners

As shown in the following diagram, the company leverages AWS messaging services to integrate these distributed systems.

  • Firstly, an SNS topic named “Orders” was created to take all orders placed by buyers on the requisition system.
  • Secondly, two Amazon SQS queues, named “Lab-Orders-AP” and “Lab-Orders-EU” (for Asia Pacific and Europe respectively), were created to backlog orders that are up for review on the approval systems.
  • Lastly, an SQS queue named “Common-Orders” was created to backlog orders that aren’t related to lab supplies, which can already be picked up by shipping partners on the fulfillment system.

The company also uses AWS Lambda functions to automatically process lab supply orders that don’t require approval or which are invalid.

In this example, because different types of orders have been published to the SNS topic, the subscribing endpoints have had to set advanced filter policies on their SNS subscriptions, to have SNS automatically filter out orders they can’t deal with.

As depicted in the above diagram, the following five filter policies have been created:

  • The SNS subscription that points to the SQS queue “Lab-Orders-AP” sets a filter policy that matches lab supply orders, with a total value greater than $1,000, and that target Asia Pacific labs only. These more expensive transactions require an approver to review orders placed by buyers.
  • The SNS subscription that points to the SQS queue “Lab-Orders-EU” sets a filter policy that matches lab supply orders, also with a total value greater than $1,000, but that target European labs instead.
  • The SNS subscription that points to the Lambda function “Lab-Preapproved” sets a filter policy that only matches lab supply orders that aren’t as expensive, up to $1,000, regardless of their target lab location. These orders simply don’t require approval and can be automatically processed.
  • The SNS subscription that points to the Lambda function “Lab-Cancelled” sets a filter policy that only matches lab supply orders with total value of $0 (zero), regardless of their target lab location. These orders carry no actual items, obviously need neither approval nor fulfillment, and as such can be automatically canceled.
  • The SNS subscription that points to the SQS queue “Common-Orders” sets a filter policy that blacklists lab supply orders. Hence, this policy matches only office and tech supply orders, which have a more streamlined fulfillment process, and require no approval, regardless of price or target location.

After the company finished building this advanced pub/sub architecture, they were then able to launch their internal procurement system and allow buyers to begin placing orders. The diagram above shows six example orders published to the SNS topic. Each order contains message attributes that describe the order, and cause them to be filtered in a different manner, as follows:

  • Message #1 is a lab supply order, with a total value of $15,700 and targeting a research lab in Singapore. Because the value is greater than $1,000, and the location “Asia-Pacific-Southeast” matches the prefix “Asia-Pacific-“, this message matches the first SNS subscription and is delivered to SQS queue “Lab-Orders-AP”.
  • Message #2 is a lab supply order, with a total value of $1,833 and targeting a research lab in Ireland. Because the value is greater than $1,000, and the location “Europe-West” matches the prefix “Europe-“, this message matches the second SNS subscription and is delivered to SQS queue “Lab-Orders-EU”.
  • Message #3 is a lab supply order, with a total value of $415. Because the value is greater than $0 and less than $1,000, this message matches the third SNS subscription and is delivered to Lambda function “Lab-Preapproved”.
  • Message #4 is a lab supply order, but with a total value of $0. Therefore, it only matches the fourth SNS subscription, and is delivered to Lambda function “Lab-Cancelled”.
  • Messages #5 and #6 aren’t lab supply orders actually; one is an office supply order, and the other is a tech supply order. Therefore, they only match the fifth SNS subscription, and are both delivered to SQS queue “Common-Orders”.

Although each message only matched a single subscription, each was tested against the filter policy of every subscription in the topic. Hence, depending on which attributes are set on the incoming message, the message might actually match multiple subscriptions, and multiple deliveries will take place. Also, it is important to bear in mind that subscriptions with no filter policies catch every single message published to the topic, as a blank filter policy equates to a catch-all behavior.

Summary

Amazon SNS allows for both string and numeric filtering operators. As explained in this post, string operators allow for exact, prefix, and “anything-but” comparisons, while numeric operators allow for exact and range comparisons. These advanced filtering operators bring even more power and flexibility to your pub/sub messaging functionality and also allow you to simplify your architecture further by removing even more logic from your subscribers.

Message filtering can be implemented easily with existing AWS SDKs by applying message and subscription attributes across all SNS supported protocols (Amazon SQS, AWS Lambda, HTTP, SMS, email, and mobile push). SNS filtering operators for numeric matching, prefix matching, and blacklisting are available now in all AWS Regions, for no extra charge.

To experiment with these new filtering operators yourself, and continue learning, try the 10-minute Tutorial Filter Messages Published to Topics. For more information, see Filtering Messages with Amazon SNS in the SNS documentation.

The Challenges of Opening a Data Center — Part 2

Post Syndicated from Roderick Bauer original https://www.backblaze.com/blog/factors-for-choosing-data-center/

Rows of storage pods in a data center

This is part two of a series on the factors that an organization needs to consider when opening a data center and the challenges that must be met in the process.

In Part 1 of this series, we looked at the different types of data centers, the importance of location in planning a data center, data center certification, and the single most expensive factor in running a data center, power.

In Part 2, we continue to look at factors that need to considered both by those interested in a dedicated data center and those seeking to colocate in an existing center.

Power (continued from Part 1)

In part 1, we began our discussion of the power requirements of data centers.

As we discussed, redundancy and failover is a chief requirement for data center power. A redundantly designed power supply system is also a necessity for maintenance, as it enables repairs to be performed on one network, for example, without having to turn off servers, databases, or electrical equipment.

Power Path

The common critical components of a data center’s power flow are:

  • Utility Supply
  • Generators
  • Transfer Switches
  • Distribution Panels
  • Uninterruptible Power Supplies (UPS)
  • PDUs

Utility Supply is the power that comes from one or more utility grids. While most of us consider the grid to be our primary power supply (hats off to those of you who manage to live off the grid), politics, economics, and distribution make utility supply power susceptible to outages, which is why data centers must have autonomous power available to maintain availability.

Generators are used to supply power when the utility supply is unavailable. They convert mechanical energy, usually from motors, to electrical energy.

Transfer Switches are used to transfer electric load from one source or electrical device to another, such as from one utility line to another, from a generator to a utility, or between generators. The transfer could be manually activated or automatic to ensure continuous electrical power.

Distribution Panels get the power where it needs to go, taking a power feed and dividing it into separate circuits to supply multiple loads.

A UPS, as we touched on earlier, ensures that continuous power is available even when the main power source isn’t. It often consists of batteries that can come online almost instantaneously when the current power ceases. The power from a UPS does not have to last a long time as it is considered an emergency measure until the main power source can be restored. Another function of the UPS is to filter and stabilize the power from the main power supply.

Data Center UPS

Data center UPSs

PDU stands for the Power Distribution Unit and is the device that distributes power to the individual pieces of equipment.

Network

After power, the networking connections to the data center are of prime importance. Can the data center obtain and maintain high-speed networking connections to the building? With networking, as with all aspects of a data center, availability is a primary consideration. Data center designers think of all possible ways service can be interrupted or lost, even briefly. Details such as the vulnerabilities in the route the network connections make from the core network (the backhaul) to the center, and where network connections enter and exit a building, must be taken into consideration in network and data center design.

Routers and switches are used to transport traffic between the servers in the data center and the core network. Just as with power, network redundancy is a prime factor in maintaining availability of data center services. Two or more upstream service providers are required to ensure that availability.

How fast a customer can transfer data to a data center is affected by: 1) the speed of the connections the data center has with the outside world, 2) the quality of the connections between the customer and the data center, and 3) the distance of the route from customer to the data center. The longer the length of the route and the greater the number of packets that must be transferred, the more significant a factor will be played by latency in the data transfer. Latency is the delay before a transfer of data begins following an instruction for its transfer. Generally latency, not speed, will be the most significant factor in transferring data to and from a data center. Packets transferred using the TCP/IP protocol suite, which is the conceptual model and set of communications protocols used on the internet and similar computer networks, must be acknowledged when received (ACK’d) and requires a communications roundtrip for each packet. If the data is in larger packets, the number of ACKs required is reduced, so latency will be a smaller factor in the overall network communications speed.

Latency generally will be less significant for data storage transfers than for cloud computing. Optimizations such as multi-threading, which is used in Backblaze’s Cloud Backup service, will generally improve overall transfer throughput if sufficient bandwidth is available.

Those interested in testing the overall speed and latency of their connection to Backblaze’s data centers can use the Check Your Bandwidth tool on our website.
Data center telecommunications equipment

Data center telecommunications equipment

Data center under floor cable runs

Data center under floor cable runs

Cooling

Computer, networking, and power generation equipment generates heat, and there are a number of solutions employed to rid a data center of that heat. The location and climate of the data center is of great importance to the data center designer because the climatic conditions dictate to a large degree what cooling technologies should be deployed that in turn affect the power used and the cost of using that power. The power required and cost needed to manage a data center in a warm, humid climate will vary greatly from managing one in a cool, dry climate. Innovation is strong in this area and many new approaches to efficient and cost-effective cooling are used in the latest data centers.

Switch's uninterruptible, multi-system, HVAC Data Center Cooling Units

Switch’s uninterruptible, multi-system, HVAC Data Center Cooling Units

There are three primary ways data center cooling can be achieved:

Room Cooling cools the entire operating area of the data center. This method can be suitable for small data centers, but becomes more difficult and inefficient as IT equipment density and center size increase.

Row Cooling concentrates on cooling a data center on a row by row basis. In its simplest form, hot aisle/cold aisle data center design involves lining up server racks in alternating rows with cold air intakes facing one way and hot air exhausts facing the other. The rows composed of rack fronts are called cold aisles. Typically, cold aisles face air conditioner output ducts. The rows the heated exhausts pour into are called hot aisles. Typically, hot aisles face air conditioner return ducts.

Rack Cooling tackles cooling on a rack by rack basis. Air-conditioning units are dedicated to specific racks. This approach allows for maximum densities to be deployed per rack. This works best in data centers with fully loaded racks, otherwise there would be too much cooling capacity, and the air-conditioning losses alone could exceed the total IT load.

Security

Data Centers are high-security facilities as they house business, government, and other data that contains personal, financial, and other secure information about businesses and individuals.

This list contains the physical-security considerations when opening or co-locating in a data center:

Layered Security Zones. Systems and processes are deployed to allow only authorized personnel in certain areas of the data center. Examples include keycard access, alarm systems, mantraps, secure doors, and staffed checkpoints.

Physical Barriers. Physical barriers, fencing and reinforced walls are used to protect facilities. In a colocation facility, one customers’ racks and servers are often inaccessible to other customers colocating in the same data center.

Backblaze racks secured in the data center

Backblaze racks secured in the data center

Monitoring Systems. Advanced surveillance technology monitors and records activity on approaching driveways, building entrances, exits, loading areas, and equipment areas. These systems also can be used to monitor and detect fire and water emergencies, providing early detection and notification before significant damage results.

Top-tier providers evaluate their data center security and facilities on an ongoing basis. Technology becomes outdated quickly, so providers must stay-on-top of new approaches and technologies in order to protect valuable IT assets.

To pass into high security areas of a data center requires passing through a security checkpoint where credentials are verified.

Data Center security

The gauntlet of cameras and steel bars one must pass before entering this data center

Facilities and Services

Data center colocation providers often differentiate themselves by offering value-added services. In addition to the required space, power, cooling, connectivity and security capabilities, the best solutions provide several on-site amenities. These accommodations include offices and workstations, conference rooms, and access to phones, copy machines, and office equipment.

Additional features may consist of kitchen facilities, break rooms and relaxation lounges, storage facilities for client equipment, and secure loading docks and freight elevators.

Moving into A Data Center

Moving into a data center is a major job for any organization. We wrote a post last year, Desert To Data in 7 Days — Our New Phoenix Data Center, about what it was like to move into our new data center in Phoenix, Arizona.

Desert To Data in 7 Days — Our New Phoenix Data Center

Visiting a Data Center

Our Director of Product Marketing Andy Klein wrote a popular post last year on what it’s like to visit a data center called A Day in the Life of a Data Center.

A Day in the Life of a Data Center

Would you Like to Know More about The Challenges of Opening and Running a Data Center?

That’s it for part 2 of this series. If readers are interested, we could write a post about some of the new technologies and trends affecting data center design and use. Please let us know in the comments.

Here's a tip!Here’s a tip on finding all the posts tagged with data center on our blog. Just follow https://www.backblaze.com/blog/tag/data-center/.

Don’t miss future posts on data centers and other topics, including hard drive stats, cloud storage, and tips and tricks for backing up to the cloud. Use the Join button above to receive notification of future posts on our blog.

The post The Challenges of Opening a Data Center — Part 2 appeared first on Backblaze Blog | Cloud Storage & Cloud Backup.