Category: Internet security

When Convenience Creates Risk: Taking a Deeper Look at Security Code AutoFill on iOS 12 and macOS Mojave

A flaw in Apple’s Security Code AutoFill feature can affect a wide range of services, from online banking to instant messaging.

In June 2018, we reported a problem in the iOS 12 beta. In the previous post, we discussed the associated risks the problem creates for transaction authentication technology used in online banking and elsewhere. We described the underlying issue and that the risk will carry over to macOS Mojave. Since our initial reports, Apple has modified the Security Code AutoFill feature, but the problem is not yet solved.

In this blog post, we publish the results of our extended analysis and demonstrate that the changes made by Apple mitigated one symptom of the problem, but did not address the cause. Security Code AutoFill could leave Apple users in a vulnerable position after upgrading to iOS 12 and macOS Mojave, exposing them to risks beyond the scope of our initial reports.

We describe four example attacks that are intended to demonstrate the risks stemming from the flawed Security Code AutoFill, but intentionally omit the detail necessary to execute them against live systems. Note that supporting screenshots and videos in this article may identify companies whose services we’ve used to test our attacks. We do not infer that those companies’ systems would be affected any more or any less than their competitors.

Flaws in Security Code AutoFill

The Security Code AutoFill feature extracts short security codes (e.g., a one-time password or OTP) from an incoming SMS and allows the user to autofill that code into a web form, webpage, or app when authenticating. This feature is meant to provide convenience, as the user no longer needs to memorize and re-enter a code in order to authenticate. However, this convenience could create risks for the user.

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Stronger Password, Longer Lifetime: Studying UCL’s password policy

In October 2016, UCL’s Information Services Division (ISD) implemented a new password policy to encourage users to choose stronger passwords. The policy links password lifetime (the time before the password expires) to password strength: The stronger the password, the longer the lifetime.

We (Ingolf Becker, Simon Parkin and M. Angela Sasse) decided to collaborate with the Information Services Division to study the effect of this policy change, and the results were published at USENIX Security this week. We find that users appreciate the choice and respond to the policy by choosing stronger passwords when changing passwords. Even after 16 months the mean password lifetime at UCL continues to increase, yet stronger passwords also lead to more password resets.

The new policy

In the new policy, passwords with Shannon Information Entropy of 50 bits receive a lifetime of 100 days, and passwords with 120 bits receive a lifetime of 350 days:

Password expiry by entropy

Additionally, the new policy penalises the lifetime of passwords containing words from a large dictionary.

Users play the game

We analysed the password lifetime – what we will refer to from here on in as the ‘password strength’ – of all password change and reset events of all pseudonymised users at UCL. The following figure shows the mean password expiration of all users over time, smoothed by 31-day moving averages:

Password expiration over time for all users and new users.

A small drop in password strength was observed between November ’16 and February ’17, as users were moved on to and generally became accustomed to the new system; the kinds of passwords they would have been used to using were at that point not getting them as many days as before (hence the drop). After February ’17, the mean strength increases from 145 days to 170 days in 12 months – an increase of 6.9 bits of entropy. This strongly suggests that users have generally adapted slowly to the new password policy, and eventually make use of the relatively new ability to increase password lifetime by expanding and strengthening their passwords.

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What can infosec learn from strategic theory?

Antonio Roque, of MIT Lincoln Labs, has published some provocative papers to arXiv over the last year. These include one on cybersecurity meta-methodology and one on making predictions in cybersecurity. These papers ask some good questions. The one I want to focus on in this short space is what cybersecurity can learn from Carl von Clausewitz’s treatise On War.

This might seem a bit odd to modern computer scientists, but I think it’s a plausible question. Cybersecurity is about winning conflicts, at least sometimes. And as I and others have written, one of the interesting challenges about generating knowledge with a science of security is the fact we have active adversaries. As Roque tells us, generating knowledge in the face of adversaries is also one of the things On War is about.

One important question for me is whether Clausewitz interestingly presaged our current problems (and has since been overtaken), or if On War makes contributions to thinking about cybersecurity that are new and comparable to those from the fields of economics, mathematics, philosophy of science, etc. After a close reading of these papers, my stance is: I have more questions that need answers.

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Attack papers are case studies

We should treat attack papers like case studies. When we read them, review them, use them for evidence, and learn from them. This claim is not derogatory. Case studies are useful. But like anything, to be useful case studies need to be done and used appropriately.

Let’s be clear what I mean by attack paper. Any paper that reports how to attack some system. Any paper that includes details of an exploit, discloses a vulnerability, or demonstrates a proof-of-concept for breaching the security of a system. The efail paper that Steven discussed recently is an example. Security conferences are full of these; the ratio of attack papers to total papers varies per conference. USENIX Security tends to contain a fair few.

Let’s be clear what I mean by case study. I mean a scientific report that details a specific occurrence of interest as observed by the author. Case studies can be active, and include interviews or other questioning. They can be solely passive observation. Case studies can follow just one case in isolation, or might follow a series of related cases in similar ways for comparison. Case studies usually do not involve a planned intervention by the observer, otherwise we start to call them experiments. But they may track changes as the result of interventions outside the observer’s control.

What might change if we think about attack papers as case studies? We can apply our scientific experience from other disciplines. I’ve argued before that security is a science. We need to adapt scientific techniques, and other sciences might learn from what we do in security. But we need to be in a dialogue there. Calling attack papers what they are opens up this dialogue in several ways.

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Scanning the Internet for Liveness

Internet-wide scanning (or probing) has emerged as a key measurement technique to study a diverse set of the Internet’s properties, including address space utilization, host reachability, topology, service availability, vulnerabilities, and service discrimination. But despite its widespread use and critical importance for Internet measurement, we still lack a clear understanding of IP liveness—whether a target IP address responds to a probe packet. What type of probe packets should we send if we, for example, want to maximize the responding host population? What type of responses can we expect and which factors determine such responses? What degree of consistency can we expect when probing the same host with different probe packets?

In our recent paper Scanning the Internet for Liveness, we presented a systematic analysis of liveness and how it shows up in active scanning campaigns. We developed a taxonomy of liveness which we employed to develop a method to perform concurrent IPv4 scans using ICMP, five TCP-based, and two UDP-based protocols, capturing all responses to our probes. Our key findings are:

  • Responsive host populations are highly sensitive to the choice of probe. While ICMP discovers the highest number of raw IPs, our TCP and UDP measurements exclusively contribute a fifth to the total population of responsive hosts.
  • Collecting ICMP Error messages for TCP and UDP scans increases the responsive population by more than 13%, and provides new opportunities to interpret scan results.
  • At the transport layer, our concurrent measurements reveal that the majority of hosts exhibit inconsistent behaviour when probed on different ports, and that capturing negative responses significantly improves scanning completeness.
  • Our concurrent scans allow us to identify nearly 2M tarpits (IPs masquerading as fake hosts) that would bias measurements that do not take them into account.
  • Our study of cross-protocol liveness shows that responsiveness for some protocols is correlated, suggesting that the same seed set of responsive IP addresses can be potentially used to bootstrap multiple highly-correlated target populations to reduce scan traffic.

This work recently appeared in the April 2018 issue of ACM SIGCOMM Computer Communication Review (CCR), and was conducted in collaboration with Philipp Richter (MIT), Mobin Javed (LUMS Pakistan, ICSI Berkeley), Srikanth Sundaresan (Princeton University), Zakir Durumeric (Stanford University), Steven J. Murdoch (University College London), Richard Mortier (University of Cambridge) and Vern Paxson (UC Berkeley, ICSI Berkeley). Overall, this study yields practical insights and methodological improvements for the design and the execution of active Internet measurement studies. We released the code and data of this work as open source to allow for reproducibility of the results, and to enable further research.

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Tampering with OpenPGP digitally signed messages by exploiting multi-part messages

The EFAIL vulnerability in the OpenPGP and S/MIME secure email systems, publicly disclosed yesterday, allows an eavesdropper to obtain the contents of encrypted messages. There’s been a lot of finger-pointing as to which particular bit of software is to blame, but that’s mostly irrelevant to the people who need secure email. The end result is that users of encrypted email, who wanted formatting better than what a mechanical typewriter could offer, were likely at risk.

One of the methods to exploit EFAIL relied on the section of the email standard that allows messages to be in multiple parts (e.g. the body of the message and one or more attachments) – known as MIME (Multipurpose Internet Mail Extensions). The authors of the EFAIL paper used the interaction between MIME and the encryption standard (OpenPGP or S/MIME as appropriate) to cause the email client to leak the decrypted contents of a message.

However, not only can MIME be used to compromise the secrecy of messages, but it can also be used to tamper with digitally-signed messages in a way that would be difficult if not impossible for the average person to detect. I doubt I was the first person to discover this, and I reported it as a bug 5 years ago, but it still seems possible to exploit and I haven’t found a proper description, so this blog post summarises the issue.

The problem arises because it is possible to have a multi-part email where some parts are signed and some are not. Email clients could have adopted the fail-safe option of considering such a mixed message to be malformed and therefore treated as unsigned or as having an invalid signature. There’s also the fail-open option where the message is considered signed and both the signed and unsigned parts are displayed. The email clients I looked at (Enigmail with Mozilla Thunderbird, and GPGTools with Apple Mail) opt for a variant of the fail-open approach and thus allow emails to be tampered with while keeping their status as being digitally signed.

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Thinking about fake news – As a security incident?

In Tristan and David’s Philosophy, Politics and Economics of Security and Privacy class, Jono gave a little information about incident response.  As a result, we have been thinking about the recent furor over fake news. There are some big questions circling this topic, and we’re going to try to focus on a part we have some competence in: what an understanding of fake news as a security incident can contribute to the wider debate. Our goal here is mostly to highlight some lessons from security research that should be applicable, so we can help constrain the solution space. Ultimately, any solution will need to engage with wider civil society.

The lessons we will argue for in the following are:

  • Solutions need to support the elector’s primary task. Education to avoid cognitive biases is not a short- or medium-term solution.
  • Focus on aligning the incentives of the media companies and the voters. Reduce the return on investment for the adversary.
  • Any blocking should be strategically useful, and not merely reactionary.

First, we want a more specific term, as well as a less charged one. Fake news includes politically or financially motivated stories presented as factual reports on the world that are fictional in material ways, and usually are intended to stir strong feelings. This definition is hardly complete. Furthermore, similar to the term “post-truth” as discussed by Jasanoff and Simmet, the term “fake news” makes several value judgement we’d like to avoid. “Fake news” carries a strong suggestion that we, the speakers, know what is true and what isn’t, and it also indicates some condescension by the speaker for anyone who believes an item of fake news. We want to avoid such insults. Instead, let’s say we want to focus on the following hypothetical security policy: democratic elections should be free from foreign interference.

Grounding out this policy definition hangs on the term “interference.” This is hard. Ultimately, the will of an elector in a free and fair election needs to be respected. This makes it particularly challenging to agree on constraints to what information an elector has access to. In practice, no elector is omniscient, so some constraints de facto exist. But weighing in on this issue is outside our competence. Let’s assume for now that public policy will provide an assessment of “interference” eventually. The UK recently announced a “dedicated national security communications unit” would be charged with “combating disinformation by state actors and others.” In France, Emmanuel Macron plans legislation to fight interference from foreign sources during elections. Various social media platforms have likewise announced attempted fixes, which means they have some functional definition of what “interference” they’re seeking to remove. Unfortunately, “none of the tech giants claim to be ready” for the November 2018 elections in the US.

Interference in elections is a type of information warfare. An appropriate security policy needs to assess the threat environment and the capabilities of the adversaries. In particular, the Russian Federation has been assessed as a highly motivated and well-resourced actor in this space. We should note that Russia, in turn, assesses the intent and capability of the USA similarly. Tools and tactics within information warfare, particularly disinformation campaigns, help define “interference” within our security policy.

In this context, what can the security research community recommend? Well, the main target of the disinformation campaign are usual citizens. They are targetable largely due to inherent cognitive biases in the way humans process and reason about information. In security terms, we could see these biases as vulnerabilities in the system. Classically, we have two options to secure the system: patch the vulnerability, or prevent the adversary from exploiting it by controlling or filtering the attack before it reaches the target.

Patch in this case would mean teaching people to avoid cognitive biases in their day-to-day reasoning. Psychology tells us this is hard. Intelligence analysts train for months or years for this. And the research in usable security has affirmed time and time again that the users are not the enemy. That is, the system must alleviate the burden on the user’s attention and not interfere with their primary task, or else the user will subvert or avoid the protections put in place. Any changes in user culture are slow. This leads us to lesson 1 on preventing disinformation campaigns for election interference: solutions need to support the elector’s primary task. Education to avoid cognitive biases is not a short-term or medium-term solution.

Controlling the attack vectors is more promising, although filtering them is not. A key aspect of any information security policy is aligning the economic incentives of the actors. Economics is a main reason why infosec is hard. It may not be easy to reorganize the incentives in the advertising and news distribution media space. However, as long as organizations profit from more clicks on an article no matter the content, there will be an incentive to drive viewers that is ultimately at cross-purposes with our security goal. Such misaligned incentives often swamp any technical security solutions. And any adversary with an economic incentive to attack usually will. Thus our second lesson: focus on aligning the incentives of the media companies and the voters; reduce the return on investment for the adversary. Exactly how to do these things will require future work.

There are huge issues about human rights and free speech for blocking access to information. However, the technical aspects of blacklisting are worth understanding before even attempting such human-rights debates. Blacklists of internet resources, such as domain names, IP addresses, or web pages, are useful. But they’re not a final solution. Whether blacklists move at the speed of national legislatures or are updated every five minutes, their main impact is to cause the adversary to move around.  Blacklists alone are not enough. We would need to look for suspiciously mobile resources (i.e. fast-flux), and eventually whitelist resources. Blacklists such as implemented by Facebook in response to Congress are helpful. But we should carefully consider how they drive the disinformation campaigns into a place we are better able to counteract them, and be sure we don’t make such campaigns harder to find instead. Lesson 3 is therefore that any blocking should be strategically useful, and not merely reactionary.

We’d be happy for further comments on fake news, disinformation campaigns that interfere with elections, lessons we’ve missed, disagreements about the value of security research to this topic, and other comments you might have! This is a wide open topic, and we’re still sounding it all out.

Practicing a science of security

Recently, at NSPW 2017, Tyler Moore, David Pym, and I presented our work on practicing a science of security. The main argument is that security work – both in academia but also in industry – already looks a lot like other sciences. It’s also an introduction to modern philosophy of science for security, and a survey of the existing science of security discussion within computer science. The goal is to help us ask more useful questions about what we can do better in security research, rather than get distracted by asking whether security can be scientific.

Most people writing about a science of security conclude that security work is not a science, or at best rather hopefully conclude that it is not a science yet but could be. We identify five common reasons people present as to why security is not a science: (1) experiments are untenable; (2) reproducibility is impossible; (3) there are no laws of nature in security; (4) there is no single ontology of terms to discuss security; and (5) security is merely engineering.

Through our introduction to modern philosophy of science, we demonstrate that all five of these complaints are misguided. They rely on an old conception of what counts as science that was largely abandoned in the 1970s, when the features of biology came to be recognized as important and independent from the features of physics. One way to understand what the five complaints actually allege is that security is not physics. But that’s much less impactful than claiming it is not science.

More importantly, we have a positive message on how to overcome these challenges and practice a science of security. Instead of complaining about untenable experiments, we can discuss structured observations of the empirical world. Experiments are just one type of structured observation. We need to know what counts as a useful structure to help us interpret the results as evidence. We provide recommendations for use of randomized control trials as well as references for useful design of experiments that collect qualitative empirical data. Ethical constraints are also important; the Menlo Report provides a good discussion on addressing them when designing structured observations and interventions in security.

Complaints about reproducibility are really targeted at the challenge of interpreting results. Astrophysics and paleontology do not reproduce experiments either, but are clearly still sciences. There are different senses of “reproduce,” from repeat exactly to corroborate by similar observations in a different context. There are also notions of statistical reproducibility, such as using the right tests and having enough observations to justify a statistical claim. The complaint is unfair in essentially demanding all the eight types of reproducibility at once, when realistically any individual study will only be able to probe a couple types at best. Seen with this additional nuance, security has similar challenges in reproducibility and interpreting evidence as other sciences.

A law of nature is a very strange thing to ask for when we have constructed the devices we are studying. The word “law” has had a lot of sticking power within science. The word was perhaps used in the 1600s and 1700s to imply a divine designer, thereby making the Church more comfortable with the work of the early scientists. The intellectual function we really care about is that a so-called “law” lets us generalize from particular observations. Mechanistic explanations of phenomena provide a more useful and approachable goal for our generalizations. A mechanism “for a phenomenon consists of entities (or parts) whose activities and interactions are organized so as to be responsible for the phenomenon” (pg 2).

MITRE wrote the original statement that a single ontology was needed for a science of security. They also happen to have a big research group funded to create such an ontology. We synthesize a more realistic view from Galison, Mitchell, and Craver. Basically, diverse fields contribute to a science of security by collaboratively adding constraints on the available explanations for a phenomenon. We should expect our explanations of complex topics to reflect that complexity, and so complexity may be a mark of maturity, rather than (as is commonly taken) a mark that security has as yet failed to become a science by simplifying everything into one language.

Finally, we address the relationship between science and engineering. In short, people have tried to reduce science to engineering and engineering to science. Neither are convincing. The line between the two is blurry, but it is useful. Engineers generate knowledge, and scientists generate knowledge. Scientists tend to want to explain why, whereas engineers tend to want to predict a change in the future based on something they make.  Knowing why may help us make changes. Making changes may help us understand why. We draw on the work of Dear and Leonelli to bring out this nuanced, mutually supportive relationship between science and engineering.

Security already can accommodate all of these perspectives. There is nothing here that makes it seem any less scientific than life sciences. What we hope to gain from this reorientation is to refocus the question about cybersecurity research from ‘is this process scientific’ to ‘why is this scientific process producing unsatisfactory results’.

Should you phish your own employees?

No. Please don’t. It does little for security but harms productivity (because staff spend ages pondering emails, and not answering legitimate ones), upsets staff and destroys trust within an organisation.

Why is phishing a problem?

Phishing is one of the more common ways by which criminals gain access to companies’ passwords and other security credentials. The criminal sends a fake email to trick employees into opening a malware-containing attachment, clicking on a link to a malicious website that solicits passwords, or carrying out a dangerous action like transferring funds to the wrong person. If the attack is successful, criminals could impersonate staff, gain access to confidential information, steal money, or disrupt systems. It’s therefore understandable that companies want to block phishing attacks.

Perimeter protection, such as blocking suspicious emails, can never be 100% accurate. Therefore companies often tell employees not to click on links or open attachments in suspicious emails.

The problem with this advice is that it conflicts with how technology works and employees getting their job done. Links are meant to be clicked on, attachments are meant to be opened. For many employees their job consists almost entirely of opening attachments from strangers, and clicking on links in emails. Even a moderately well targeted phishing email will almost certainly succeed in getting some employees to click on it.

Companies try to deal with this problem through more aggressive training, particularly sending out mock phishing emails that exhibit some of the characteristics of phishing emails but actually come from the IT staff at the company. The company then records which employees click on the link in the email, open the attachment, or provide passwords to a fake website, as appropriate.

The problem is that mock-phishing causes more harm than good.

What harm does mock-phishing cause?

I hope no company would publicly name and shame employees that open mock-phishing emails, but effectively telling your staff that they failed a test and need remedial training will make them feel ashamed despite best intentions. If, as often recommended, employees who repeatedly open mock-phishing emails will even be subject to disciplinary procedures, not only will mock phishing lead to stress and consequent loss of productivity, but it will make it less likely that employees will report when they have clicked on a real phishing email.

Alienating your employees in this way is really the last thing a company should do if it wants to be secure – something Adams & Sasse pointed out as early as 1999. It is extremely important that companies learn when a phishing email has been opened, because there is a lot that can be done to prevent or limit harm. Contrary to popular belief, attacks don’t generally happen “at the speed of light” (it took three weeks for the Target hackers to steal data, from the point of the initial breach). Promptly cleaning potentially infected computers, revoking compromised credentials, and analysing network logs, is extremely effective, but works only if employees feel that they are on the same side as IT staff.

More generally, mock-phishing conflicts with and harms the trust relationship between the company and employees (because the company is continually probing them for weakness) and between employees (because mock-phishing normally impersonates fellow employees). Kirlappos and Sasse showed that trust is essential for maintaining employee satisfaction and for creating organisational resilience, including ability to comply with security policies. If unchecked, prolonged resentment within organisation achieves exactly the opposite – it increases the risk of insider attacks, which in the vast majority of cases start with disgruntlement.

There are however ways to achieve the same goals as mock phishing without the resulting harm.

Measuring resilience against phishing

Companies are right to want to understand how vulnerable they are to attack, and mock-phishing seems to offer this. One problem however is that the likelihood of opening a phishing email depends mainly on how well it is written, and so mock-phishing campaigns tell you more about the campaign than the organisation.

Instead, because every organisation inevitably receives many phishing emails, companies don’t need to send out their own. Use “genuine” phishing emails to collect the data needed, but be careful not to deter reporting. Realistically, however, phishing emails are going to be opened regardless of what steps are taken (short of cutting off Internet email completely). So organisations’ security strategy should accommodate this.

Reducing vulnerability to phishing

Following mock-phishing with training seems like the perfect time to get employees’ attention, but is this actually an ineffective way to reduce an organisations’ vulnerability to phishing. Caputo et. al tried this out and found that training had no significant effect, regardless of how it was phrased (using the latest nudging techniques from behavioural economists, an idea many security practitioners find very attractive). In this study, the organisation’s help desk staff was overwhelmed by calls from panicked employees – and when told it was a “training exercise”, many expressed frustration and resentment towards the security staff that had tricked them. Even if phishing prevention training could be made to work, because the activity of opening a malicious email is so close to what people do as part of their job, it would disrupt business by causing employees to delete legitimate email or spend too long deciding whether to open them.

A strong, unambiguous, and reliable cue that distinguishes phishing emails from legitimate ones would help, but until we have secure end-to-end encrypted and authenticated email, this isn’t possible. We are left with the task of designing security systems accepting that some phishing emails will be opened, rather than pretending they won’t be and blaming breaches on employees that fail to meet an unachievable bar. If employees are consistently being told that their behaviour is not good enough but not being given realistic and actionable advice on how to do better, it creates learned helplessness, with all the negative psychological consequences.

Comply with industry “best-practice”

Something must be done to protect the company; mock-phishing is something, therefore must must be done. This perverse logic is the root cause of much poor security, where organisations think they must comply with so-called “best practice” – seldom more than out-of-date folk tradition – or face penalties when there is a breach. It’s for this reason that bad security guidance persists long after it has been shown to be ineffective, such as password complexity rules.

Compliance culture, where rules are blindly followed without there being evidence of effectiveness, is one of the worst reasons to adopt a security practice. We need more research on how to develop technology that is secure and that supports an organisation’s overall goals. We know that mock-phishing is not effective, but what’s the right combination of security advice and technology that will give adequate protection, and how do we adapt these to the unique situation of each company?

What to do instead?

The security industry should take the lead of the aerospace industry and recognise the “blame and train” isn’t an effective or acceptable strategy. The attraction of mock phishing exercises to security staff is that they can say they are “doing something”, and like the idea of being able to measure behaviour change as a result of it – even though research points the other way. If vendors claim they have examples of mock phishing training reducing clicks on links, it is usually because employees have been trained to recognise only the vendor’s mock phishing emails or are frightened into not clicking on any links – and nobody measures the losses that occur because emails from actual or potential customers or suppliers are not answered. “If security doesn’t work for people, it doesn’t work.”

When the CIO of a merchant bank found that mock phishing caused much anger and resentment from highly paid traders, but no reduction in clicking on links, he started to listen to what it looked like from their side. “Your security specialists can’t tell if it is a phishing email or not – why are you expecting me to be able to do that?” After seeing the problem from their perspective, he added a button to the corporate mail client labeled “I’m not sure” instead, and asked staff to use the button to forward emails they were not sure about to the security department. The security department then let the employee know, plus list all identified malicious emails on a web site employees could check before forwarding emails. Clicking on phishing links dropped to virtually zero – plus staff started talking to each other about phishing emails they had seen, and what the attacker was trying to do.

Security should deal with the problems that actually face the company; preventing phishing wouldn’t have stopped recent ransomware attacks. Assuming phishing is a concern then, where possible to do so with adequate accuracy, phishing emails should be blocked. Some will get through, but with well engineered and promptly patched systems, harm can be limited. Phishing-resistant authentication credentials, such as FIDO U2F, means that stolen passwords are worthless. Common processes should be designed so that the easy option is the secure one, giving people time to think carefully about whether a request for an exception is legitimate. Finally, if malware does get onto company computers, compartmentalisation will limit damage, effective monitoring facilitates detection, and good backups allow rapid recovery.

 

An earlier version of this article was previously published by the New Statesman.

Preventing phishing won’t stop ransomware spreading

Ransomware is in the news again, with Reckitt Benckiser reporting that disruption caused by the NotPetya ransomware could have cost them up to £100 million. In response to this news, just as every previous ransomware incident, the security industry started giving out advice – almost universally emphasising the importance of not opening phishing emails.

The problem is that this advice won’t work. Putting aside the fact that such advice is often so vague as to be impossible to put into action, the cause of recent ransomware outbreaks is not people opening phishing emails:

  • WannaCry, which notably caused severe disruption to the NHS, spread by automated scanning of computers vulnerable to an NSA-developed exploit. Although the starting point was initially assumed to be a phishing email, this was later debunked – only network scanning was used.
  • The Mole Ransomware attack that hit many organisations, including UCL, was initially thought to be spread by employees clicking on links in phishing emails. Subsequent analysis found this was incorrect and most likely the malware spread through malicious advertisements on legitimate websites.
  • NotPetya was initially thought to have been spread through Russian or Ukrainian phishing emails (explaining why that part of the world was so badly affected). It turned out to have not involved phishing at all, but the outbreak started through a tampered software update to the MEDoc tax accounting software mandated by the Ukranian government. Once inside an organisation, NotPetya then spread using the same exploit as WannaCry or by compromising administrative credentials.

Here are three major incidents, making international news, and the standard advice to “be vigilant” when opening emails or clicking links would have been useless. Is it any surprise that security advice gets ignored?

Not only is common anti-phishing advice unhelpful but it shifts blame to individuals (who are not in a position to prevent or mitigate most attacks) away from the IT industry and staff (who are). It also misleads management into thinking that they can “blame-and-train” their employees rather than investing in well engineered preventative security mechanisms and IT systems that can recover from compromise.

And there are things that can be done which have been shown to be effective, not just against the current outbreaks but many in the past and likely future. WannaCry would have been prevented by applying software updates, but the NotPetya outbreak was caused by a software update. The industry needs to act promptly to ensure that software updates are safe and reliable before customers become even more wary about installing them.

The spread of WannaCry and NotPetya within companies could have been prevented or slowed through better operational practices such as segmenting networks and limiting the use of administrative privilege. We’ve known this approach to be effective, but better tools and practices are needed to avoid enhanced security mechanisms being a drag on an organisation’s productivity.

Mole could have been prevented by ad-blocking browser extensions. The advertising industry is in open war against ad-blocking because it harms their income stream, but while they keep on spreading malware through their networks I have limited sympathy.

Well maintained and protected backups are essential to allow recovery, whether from ransomware, purely destructive attacks, or hardware failure. The security techniques above are effective, but these measures will not prevent every attack so mechanisms are needed to efficiently deal with the aftermath.

Most importantly we need to move away from security being a set of traditions passed from generation to generation with little or no reason to believe they are effective (so called “best practice”) to well engineered systems following rigorous, evidence-based guidance on state of the art cybersecurity principles, standards and practices.