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This is a current list of where and when I am scheduled to speak:
The list is maintained on this page.
The oceans are warmer, which means more squid.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
A detailed report of the 2021 ransomware attack against Ireland’s Health Services Executive lists some really bad security practices:
The report notes that:
- The HSE did not have a Chief Information Security Officer (CISO) or a “single responsible owner for cybersecurity at either senior executive or management level to provide leadership and direction.
- It had no documented cyber incident response runbooks or IT recovery plans (apart from documented AD recovery plans) for recovering from a wide-scale ransomware event.
- Under-resourced Information Security Managers were not performing their business as usual role (including a NIST-based cybersecurity review of systems) but were working on evaluating security controls for the COVID-19 vaccination system. Antivirus software triggered numerous alerts after detecting Cobalt Strike activity but these were not escalated. (The antivirus server was later encrypted in the attack).
- There was no security monitoring capability that was able to effectively detect, investigate and respond to security alerts across HSE’s IT environment or the wider National Healthcare Network (NHN).
- There was a lack of effective patching (updates, bug fixes etc.) across the IT estate and reliance was placed on a single antivirus product that was not monitored or effectively maintained with updates across the estate. (The initial workstation attacked had not had antivirus signatures updated for over a year.)
- Over 30,000 machines were running Windows 7 (out of support since January 2020).
- The initial breach came after a HSE staff member interacted with a malicious Microsoft Office Excel file attached to a phishing email; numerous subsequent alerts were not effectively investigated.
PwC’s crisp list of recommendations in the wake of the incident as well as detail on the business impact of the HSE ransomware attack may prove highly useful guidance on best practice for IT professionals looking to set up a security programme and get it funded.
Bunnie Huang has created a Plausibly Deniable Database.
Most security schemes facilitate the coercive processes of an attacker because they disclose metadata about the secret data, such as the name and size of encrypted files. This allows specific and enforceable demands to be made: “Give us the passwords for these three encrypted files with names A, B and C, or else…”. In other words, security often focuses on protecting the confidentiality of data, but lacks deniability.
A scheme with deniability would make even the existence of secret files difficult to prove. This makes it difficult for an attacker to formulate a coherent demand: “There’s no evidence of undisclosed data. Should we even bother to make threats?” A lack of evidence makes it more difficult to make specific and enforceable demands.
[…]
Precursor is a device we designed to keep secrets, such as passwords, wallets, authentication tokens, contacts and text messages. We also want it to offer plausible deniability in the face of an attacker that has unlimited access to a physical device, including its root keys, and a set of “broadly known to exist” passwords, such as the screen unlock password and the update signing password. We further assume that an attacker can take a full, low-level snapshot of the entire contents of the FLASH memory, including memory marked as reserved or erased. Finally, we assume that a device, in the worst case, may be subject to repeated, intrusive inspections of this nature.
We created the PDDB (Plausibly Deniable DataBase) to address this threat scenario. The PDDB aims to offer users a real option to plausibly deny the existence of secret data on a Precursor device. This option is strongest in the case of a single inspection. If a device is expected to withstand repeated inspections by the same attacker, then the user has to make a choice between performance and deniability. A “small” set of secrets (relative to the entire disk size, on Precursor that would be 8MiB out of 100MiB total size) can be deniable without a performance impact, but if larger (e.g. 80MiB out of 100MiB total size) sets of secrets must be kept, then archived data needs to be turned over frequently, to foil ciphertext comparison attacks between disk imaging events.
I have been thinking about this sort of thing for many, many years. (Here’s my analysis of one such system.) I have come to realize that the threat model isn’t as simple as Bunnie describes. The goal is to prevent “rubber-hose cryptanalysis,” simply beating the encryption key out of someone. But while a deniable database or file system allows the person to plausibly say that there are no more keys to beat out of them, the perpetrators can never be sure. The value of a normal, undeniable encryption system is that the perpetrators will know when they can stop beating the person—the person can undeniably say that there are no more keys left to reveal.
Researchers have calculated the quantum computer size necessary to break 256-bit elliptic curve public-key cryptography:
Finally, we calculate the number of physical qubits required to break the 256-bit elliptic curve encryption of keys in the Bitcoin network within the small available time frame in which it would actually pose a threat to do so. It would require 317 × 106 physical qubits to break the encryption within one hour using the surface code, a code cycle time of 1 μs, a reaction time of 10 μs, and a physical gate error of 10-3. To instead break the encryption within one day, it would require 13 × 106 physical qubits.
In other words: no time soon. Not even remotely soon. IBM’s largest ever superconducting quantum computer is 127 physical qubits.
Amy Zegart has a new book: Spies, Lies, and Algorithms: The History and Future of American Intelligence. Wired has an excerpt:
In short, data volume and accessibility are revolutionizing sensemaking. The intelligence playing field is leveling—and not in a good way. Intelligence collectors are everywhere, and government spy agencies are drowning in data. This is a radical new world and intelligence agencies are struggling to adapt to it. While secrets once conferred a huge advantage, today open source information increasingly does. Intelligence used to be a race for insight where great powers were the only ones with the capabilities to access secrets. Now everyone is racing for insight and the internet gives them tools to do it. Secrets still matter, but whoever can harness all this data better and faster will win.
The third challenge posed by emerging technologies strikes at the heart of espionage: secrecy. Until now, American spy agencies didn’t have to interact much with outsiders, and they didn’t want to. The intelligence mission meant gathering secrets so we knew more about adversaries than they knew about us, and keeping how we gathered secrets a secret too.
[…]
In the digital age, however, secrecy is bringing greater risk because emerging technologies are blurring nearly all the old boundaries of geopolitics. Increasingly, national security requires intelligence agencies to engage the outside world, not stand apart from it.
I have not yet read the book.
An actually serious scientific journal has published a paper speculating that octopus and squid could be of extraterrestrial origin.
News article.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
Senators have reintroduced the EARN IT Act, requiring social media companies (among others) to administer a massive surveillance operation on their users:
A group of lawmakers led by Sen. Richard Blumenthal (D-CT) and Sen. Lindsey Graham (R-SC) have re-introduced the EARN IT Act, an incredibly unpopular bill from 2020 that was dropped in the face of overwhelming opposition. Let’s be clear: the new EARN IT Act would pave the way for a massive new surveillance system, run by private companies, that would roll back some of the most important privacy and security features in technology used by people around the globe. It’s a framework for private actors to scan every message sent online and report violations to law enforcement. And it might not stop there. The EARN IT Act could ensure that anything hosted online—backups, websites, cloud photos, and more—is scanned.
Slashdot thread.
MIT Technology Review published an interview with Gil Herrera, the new head of the NSA’s Research Directorate. There’s a lot of talk about quantum computing, monitoring 5G networks, and the problems of big data:
The math department, often in conjunction with the computer science department, helps tackle one of NSA’s most interesting problems: big data. Despite public reckoning over mass surveillance, NSA famously faces the challenge of collecting such extreme quantities of data that, on top of legal and ethical problems, it can be nearly impossible to sift through all of it to find everything of value. NSA views the kind of “vast access and collection” that it talks about internally as both an achievement and its own set of problems. The field of data science aims to solve them.
“Everyone thinks their data is the messiest in the world, and mine maybe is because it’s taken from people who don’t want us to have it, frankly,” said Herrera’s immediate predecessor at the NSA, the computer scientist Deborah Frincke, during a 2017 talk at Stanford. “The adversary does not speak clearly in English with nice statements into a mic and, if we can’t understand it, send us a clearer statement.”
Making sense of vast stores of unclear, often stolen data in hundreds of languages and even more technical formats remains one of the directorate’s enduring tasks.
The Open Source Security Foundation announced $10 million in funding from a pool of tech and financial companies, including $5 million from Microsoft and Google, to find vulnerabilities in open source projects:
The “Alpha” side will emphasize vulnerability testing by hand in the most popular open-source projects, developing close working relationships with a handful of the top 200 projects for testing each year. “Omega” will look more at the broader landscape of open source, running automated testing on the top 10,000.
This is an excellent idea. This code ends up in all sorts of critical applications.
Log4j would be a prototypical vulnerability that the Alpha team might look for —an unknown problem in a high-impact project that automated tools would not be able to pick up before a human discovered it. The goal is not to use the personnel engaged with Alpha to replicate dependency analysis, for example.
Sidebar photo of Bruce Schneier by Joe MacInnis.