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Earlier sources: Security
Digital security protects systems, software, accounts, and information from misuse. Explore cybersecurity, vulnerabilities, threat intelligence, cryptography, privacy, and identity, with links to the underlying advisories and research.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗651 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
Verifiable quantum advantage based on polynomials with planted structures ↗
A central question in the theory of quantum advantage is whether there are quantum advantage protocols with similar resource requirements as random circuit sampling that are also verifiable just from the classical outputs of the quantum computation. Here, we develop the idea of simulation secrets for verifiable advantage. A verifier can use a simulation secret to evaluate a cross-entropy test faster than it would take a classical adversary to pass the test. We instantiate this idea using IQP circuits described by cubic polynomials with planted independent spaces. These correspond to the larges…
- arXiv · Published · First archived
CodeMimicry: Exploiting Safety Generalization Lag in Large Language Models via Structured Code Completion ↗
Large language models have achieved remarkable capabilities across diverse domains, yet their safety alignment remains vulnerable to jailbreak attacks. In this work, we identify a previously underexplored failure mode - safety generalization lag - where alignment trained predominantly on natural language fails to transfer to the code domain. We show that this lag induces a code-completion blind spot, allowing malicious intent embedded within syntactically valid code to evade safety mechanisms. To exploit this vulnerability, we propose CodeMimicry, a fully automated black-box jailbreak framewor…
- arXiv · Published · First archived
PassGPT+: Leveraging Linguistic Priors for Password Modeling ↗
Passwords remain the dominant online authentication mechanism, and understanding how humans choose them is essential for defensive strength estimation and attack simulation alike. Recent learning-based approaches such as PassGAN and PassGPT have shown that deep generative models can learn password structure directly from leaked corpora. However, both train from random initialization on password data alone. The role of linguistic prior knowledge in password modeling, and what it reveals about how humans create secrets, remains largely underexplored. Here, we address this gap with PassGPT+, whic…
- arXiv · Published · First archived
Natural Barriers to Quantum Extraction: On the Post-Quantum (In)security of (O)EKE and Masny-Rindal OT ↗
Encrypted key exchange (EKE), introduced by Bellovin and Merritt (IEEE S\&P 1992), and Masny-Rindal OT, introduced by Masny and Rindal (ACM CCS 2019), are highly-efficient methods for compiling essentially any KEM into advanced cryptographic protocols, namely password-authenticated key exchange (PAKE) and oblivious transfer (OT), by relying only on idealized symmetric-key primitives. They have become leading candidates for practically-implementable PAKE and OT due to (1) their simplicity, (2) their plug-and-play nature, allowing for flexibility in the choice of KEM, and (3) existing proofs of…
- Hacker News · Posted on Hacker News · First archived
Show HN: Paperweight – local-first, open-source email cleanup and privacy tool ↗
Hi HN, After building for 7 months, I'm excited to announce Paperweight V1. The idea is that your inbox knows who you ever interacted with and knows where your data lives. Every account you ever created, every service you signed up for, and every online purchase is connected to your email. Most people have hundreds of accounts they've forgotten about, creating security risks and privacy exposure. Paperweight scans your email history locally to fi…
- arXiv · Published · First archived
Privacy Foundations for Multi-Institutional Scientific Artificial Intelligence ↗
Scientific artificial intelligence (AI), spanning foundation models (FMs) to federated data-analysis pipelines, is becoming shared infrastructure across national laboratories, universities, hospitals, and industrial partners. This collaboration creates privacy risks whose natural unit is often an institution's participation, research strategy, or technical capability rather than a single record. Differential privacy (DP), federated learning (FL), secure computation, trusted execution, and provenance each protect parts of the stack, but their guarantees rarely compose across mixed-trust institu…
- arXiv · Published · First archived
Path-Finding, Orbit State Preparation, and the Security of Invariant Quantum Money ↗
The security of quantum money from knots, and of its generalization to invariant money, is based on the assumption that path-finding, exhibiting a sequence of moves between two equivalent objects, is hard. No proof of security from that assumption alone is known. The existing proofs add knowledge-of-path assumptions, which assert that any efficient algorithm producing two objects with the same invariant implicitly knows a path between them. No attack can refute such an assumption, and it is not known to follow from security. We ask when path-finding is the right assumption. When each equivalen…
- arXiv · Published · First archived
Security Properties of Neural Networks as Decision Problems ↗
Certifying a deployed neural network raises decision problems that the verification literature has not classified: whether the model carries a backdoor planted in its training data, whether a fault in its stored parameters can drive it into an unsafe state, whether its output leaks a private part of its input. We formalise eight such problems and classify what we can. The organising observation is a logical one. The function computed by a piecewise linear network, together with all its node values, is definable by a quantifier-free formula of real addition of size linear in the network, so a p…
- GitHub · Repository created · First archived
Bingblop/ADB-Application-Manager ↗
Privacy-first full featured application and device control using ADB/Shizuku/Wireless Debugging/Root. A swiss army knife of ADB possible features.
- arXiv · Published · First archived
Aletheia: Permission-Minimality Testing for Coding-Agent Rules ↗
Repository instruction files guide coding agents, but also expose them to prompt injection. Malicious rules can request credential access or data transfer while the agent produces a correct patch. We present Aletheia, a framework for permission-minimality testing. Aletheia translates requested authority into a typed language and synthesizes executable sandbox configurations. It runs the unchanged rule and task under full permissions and independent restrictions that remove one permission at a time. Passing independent functional tests under strictly reduced authority provides a dispensability…
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How to assess evidence about Security
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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