Author: Bruce Schneier

Wow.

It seems they all exploded simultaneously, which means they were triggered.

Were they each tampered with physically, or did someone figure out how to trigger a thermal runaway remotely? Supply chain attack? Malicious code update, or natural vulnerability?

I have no idea, but I expect we will all learn over the next few days.

EDITED TO ADD: I’m reading nine killed and 2,800 injured. That’s a lot of collateral damage. (I haven’t seen a good number as to the number of pagers yet.)

EDITED TO ADD: Reuters writes: “The pagers that detonated were the latest model brought in by Hezbollah in recent months, three security sources said.” That implies supply chain attack. And it seems to be a large detonation for an overloaded battery.

This reminds me of the 1996 assassination of Yahya Ayyash using a booby trapped cellphone.

EDITED TO ADD: I am deleting political comments. On this blog, let’s stick to the tech and the security ramifications of the threat.

Interesting social engineering attack: luring potential job applicants with fake recruiting pitches, trying to convince them to download malware. From a news article

These particular attacks from North Korean state-funded hacking team Lazarus Group are new, but the overall malware campaign against the Python development community has been running since at least August of 2023, when a number of popular open source Python tools were maliciously duplicated with added malware. Now, though, there are also attacks involving “coding tests” that only exist to get the end user to install hidden malware on their system (cleverly hidden with Base64 encoding) that allows remote execution once present. The capacity for exploitation at that point is pretty much unlimited, due to the flexibility of Python and how it interacts with the underlying OS.

This is a current list of where and when I am scheduled to speak:

  • I’m speaking at eCrime 2024 in Boston, Massachusetts, USA. The event runs from September 24 through 26, 2024, and my keynote is at 8:45 AM ET on the 24th.
  • I’m briefly speaking at the EPIC Champion of Freedom Awards in Washington, DC on September 25, 2024.
  • I’m speaking at SOSS Fusion 2024 in Atlanta, Georgia, USA. The event will be held on October 22 and 23, 2024, and my talk is  at 9:15 AM ET on October 22, 2024.

The list is maintained on this page.

Microsoft is updating SymCrypt, its core cryptographic library, with new quantum-secure algorithms. Microsoft’s details are here. From a news article:

The first new algorithm Microsoft added to SymCrypt is called ML-KEM. Previously known as CRYSTALS-Kyber, ML-KEM is one of three post-quantum standards formalized last month by the National Institute of Standards and Technology (NIST). The KEM in the new name is short for key encapsulation. KEMs can be used by two parties to negotiate a shared secret over a public channel. Shared secrets generated by a KEM can then be used with symmetric-key cryptographic operations, which aren’t vulnerable to Shor’s algorithm when the keys are of a sufficient size.

The ML in the ML-KEM name refers to Module Learning with Errors, a problem that can’t be cracked with Shor’s algorithm. As explained here, this problem is based on a “core computational assumption of lattice-based cryptography which offers an interesting trade-off between guaranteed security and concrete efficiency.”

ML-KEM, which is formally known as FIPS 203, specifies three parameter sets of varying security strength denoted as ML-KEM-512, ML-KEM-768, and ML-KEM-1024. The stronger the parameter, the more computational resources are required.

The other algorithm added to SymCrypt is the NIST-recommended XMSS. Short for eXtended Merkle Signature Scheme, it’s based on “stateful hash-based signature schemes.” These algorithms are useful in very specific contexts such as firmware signing, but are not suitable for more general uses.

New research evaluating the effectiveness of reward modeling during Reinforcement Learning from Human Feedback (RLHF): “SEAL: Systematic Error Analysis for Value ALignment.” The paper introduces quantitative metrics for evaluating the effectiveness of modeling and aligning human values:

Abstract: Reinforcement Learning from Human Feedback (RLHF) aims to align language models (LMs) with human values by training reward models (RMs) on binary preferences and using these RMs to fine-tune the base LMs. Despite its importance, the internal mechanisms of RLHF remain poorly understood. This paper introduces new metrics to evaluate the effectiveness of modeling and aligning human values, namely feature imprint, alignment resistance and alignment robustness. We categorize alignment datasets into target features (desired values) and spoiler features (undesired concepts). By regressing RM scores against these features, we quantify the extent to which RMs reward them ­ a metric we term feature imprint. We define alignment resistance as the proportion of the preference dataset where RMs fail to match human preferences, and we assess alignment robustness by analyzing RM responses to perturbed inputs. Our experiments, utilizing open-source components like the Anthropic preference dataset and OpenAssistant RMs, reveal significant imprints of target features and a notable sensitivity to spoiler features. We observed a 26% incidence of alignment resistance in portions of the dataset where LM-labelers disagreed with human preferences. Furthermore, we find that misalignment often arises from ambiguous entries within the alignment dataset. These findings underscore the importance of scrutinizing both RMs and alignment datasets for a deeper understanding of value alignment.

In 2018, Australia passed the Assistance and Access Act, which—among other things—gave the government the power to force companies to break their own encryption.

The Assistance and Access Act includes key components that outline investigatory powers between government and industry. These components include:

  • Technical Assistance Requests (TARs): TARs are voluntary requests for assistance accessing encrypted data from law enforcement to teleco and technology companies. Companies are not legally obligated to comply with a TAR but law enforcement sends requests to solicit cooperation.
  • Technical Assistance Notices (TANs): TANS are compulsory notices (such as computer access warrants) that require companies to assist within their means with decrypting data or providing technical information that a law enforcement agency cannot access independently. Examples include certain source code, encryption, cryptography, and electronic hardware.
  • Technical Capability Notices (TCNs): TCNs are orders that require a company to build new capabilities that assist law enforcement agencies in accessing encrypted data. The Attorney-General must approve a TCN by confirming it is reasonable, proportionate, practical, and technically feasible.

It’s that final one that’s the real problem. The Australian government can force tech companies to build backdoors into their systems.

This is law, but near as anyone can tell the government has never used that third provision.

Now, the director of the Australian Security Intelligence Organisation (ASIO)—that’s basically their FBI or MI5—is threatening to do just that:

ASIO head, Mike Burgess, says he may soon use powers to compel tech companies to cooperate with warrants and unlock encrypted chats to aid in national security investigations.

[…]

But Mr Burgess says lawful access is all about targeted action against individuals under investigation.

“I understand there are people who really need it in some countries, but in this country, we’re subject to the rule of law, and if you’re doing nothing wrong, you’ve got privacy because no one’s looking at it,” Mr Burgess said.

“If there are suspicions, or we’ve got proof that we can justify you’re doing something wrong and you must be investigated, then actually we want lawful access to that data.”

Mr Burgess says tech companies could design apps in a way that allows law enforcement and security agencies access when they request it without comprising the integrity of encryption.

“I don’t accept that actually lawful access is a back door or systemic weakness, because that, in my mind, will be a bad design. I believe you can ­ these are clever people ­ design things that are secure, that give secure, lawful access,” he said.

We in the encryption space call that last one “nerd harder.” It, and the rest of his remarks, are the same tired talking points we’ve heard again and again.

It’s going to be an awfully big mess if Australia actually tries to make Apple, or Facebook’s WhatsApp, for that matter, break its own encryption for its “targeted actions” that put every other user at risk.