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14 stories in the last 7d

Understanding the Usability of Cryptographic Verification Tools

Survey of Tamarin and ProVerif users reveals usability barriers: debugging non-termination, model validation, and opaque proof failures hinder cryptographic protocol verification.

The paper presents an exploratory human-centered survey of researchers, graduate students, and practitioners with hands-on experience using Tamarin, ProVerif, and related cryptographic protocol verification tools. Findings reveal usability barriers across the verification workflow, including difficulties debugging non-termination and performance issues plus the lack of systematic methods for validating formal models against real protocols. When proofs fail without concrete attacks, users commonly simplify models, add helper lemmas, and revisit modeling abstractions. Participants called for actionable diagnostics, clearer explanations of results, visualization, and automation for recurring proof tasks.

arXiv cs.CR · 2d agoResearch

IDScan Confirms Data Breach Following 153 Million Driver’s Licenses Leaked on the Dark Web

IDScan.net confirms a breach after a marketplace advertised over 153 million US and Canadian driver's licenses, possibly exfiltrated continuously for over a year.

The Louisiana identity-verification firm detected unauthorized access on or around September 1, 2026, after the 'Nexus' identity theft service on the Exploit forum began advertising 170M+ people's records, including 153M+ driver's licenses, 10M+ ID cards, 3M+ travel documents, and 579,000 medical cards. Canadian records exceed 1.1 million, and the trove includes commercial licenses, Common Access Cards, and dispensary IDs, with a record for US Defense Secretary Pete Hegseth reportedly included. Nexus operators claim continuous exfiltration for over a year, with the license count growing by nearly 400,000 in 24 hours, suggesting the intrusion may be active. The FBI's New Orleans field office has opened a formal inquiry, and IDScan.net is offering free credit monitoring.

Cyber Security News · 5d agoData breach in the wild 4 sources

MIT creates method to force AI to comply with safety rules

MIT researchers published HardFlow, a method enforcing hard safety constraints on flow-matching generative models' final outputs without retraining.

MIT researchers led by Zeyang Li and Navid Azizan developed HardFlow, a trajectory-optimization method that enforces strict, non-negotiable constraints on flow-matching generative models by checking rule satisfaction only at the final generation step. Published in IEEE TPAMI, it outperformed six rival projection and guidance methods on four simulated benchmarks including D3IL robotic manipulation, Maze2D, physical process control, and image editing. All results are simulation-only, with no independent reproduction yet reported.

Social Laws for Multi-agent Coordination in Stochastic Environments

Researchers extend social laws to stochastic, reward-based multi-agent environments, defining alpha-robustness and a verification method via Markov decision processes.

The paper extends the concept of social laws from deterministic, goal-based settings to stochastic, reward-based multi-agent environments. It introduces alpha-robustness, a measure of the guaranteed utility each agent retains while pursuing its optimal single-agent policy assuming all agents obey the social law. Robustness verification is reduced to solving a series of Markov decision processes, with empirical evaluations on toy environments.

arXiv cs.AI / cs.LG / cs.CL · 15h agoAI research

SpecGuard: Inference-Time Backdoor Detection For Free

SpecGuard detects backdoored LLM behavior at inference time using speculative decoding acceptance rates, adding no extra model computation.

Researchers propose SpecGuard, an inference-time backdoor detector that repurposes draft-token acceptance rates from speculative decoding as a detection signal at zero added model-computation cost. When a trigger shifts the target model toward attacker-controlled behavior, the clean draft model's acceptance rate changes, exposing the backdoor; the paper formalizes when this signal appears and shows suppressing it weakens the backdoor. Experiments across diverse backdoor types and model families show reliable detection, including stealthy cases invisible to input-level filters. Speculative decoding is positioned as a free, always-on monitor for frequently updated deployed models.

arXiv cs.CR · 6d agoAI safety & security 2 sources2

From Specs to Apps: Verifying and Monitoring Models of Signal and WhatsApp

Researchers use the SpecMon runtime monitor to verify WhatsApp Web and Signal Desktop against formal Signal protocol models, finding undocumented libsignal fork differences.

The paper applies SpecMon, a runtime monitoring tool, to check whether executions of WhatsApp Web and Signal Desktop conform to formal models of the Signal protocol. The authors instrument both applications and build Tamarin-compatible multiset-rewrite models, including the first model of WhatsApp Web's implementation and the most detailed model to date of Signal's original protocol. They verify authentication and secrecy properties for core Signal protocol components, show monitoring detects deliberately injected faults with low overhead, and identify previously undocumented behavioral differences between the original libsignal library and WhatsApp's fork.

arXiv cs.CR · 6d agoResearch

Why I'm still bearish on LLMs after Navier-Stokes

Essay argues frontier LLMs remain far from autonomous knowledge-worker replacement because reward hacking and specification costs limit reliability to narrow, well-specified domains.

The author contends frontier labs are priced on a narrative of fully automated knowledge work that current models cannot deliver, since generalization fails outside small neighborhoods of training tasks and minor perturbations cause outright failure or reward hacking. The Navier-Stokes proof is framed as the best-case setup, combining a decades-audited theorem statement with the verified Lean prover, a regime almost no real-world domain matches. Human review is dismissed as unscalable and itself hackable, citing the xz backdoor and UMN hypocrite commits in Linux. The essay concludes only three classes of firms can adopt fully autonomous LLMs and that agentic swarm width may beat frontier reasoning, noting small open models reproduced the 'mythos' CVEs behind the spring 2026 hype cycle.

Scaling Verification of Cryptographic Software with Aeneas, Rust, and Lean

Microsoft SymCrypt implementations of SHA-3 and ML-KEM verified in Lean via Aeneas-extracted Rust models, with AI agents writing proofs.

The paper develops a methodology for verifying production Rust cryptographic code by using Aeneas to extract pure models into Lean, avoiding low-level pointer and aliasing reasoning. Applied to Microsoft's SymCrypt, it verifies SHA-3 and ML-KEM implementations ported from C to Rust and extends SymCrypt with FrodoKEM, ML-DSA, and HPKE. A 237 KLOC Lean development establishes safety, panic-freedom, and functional correctness of 16.7 KLOC of Rust supporting post-quantum cipher suites on x86-64 and ARM. AI agents autonomously write formal proofs verified by the Lean kernel, and evaluation shows verified Rust meets SymCrypt's performance and portability requirements.

arXiv cs.CR · 2d agoResearch1

AI is exposing a security structure built for yesterday’s threats

EY's Jeffrey Sallet argues AI-driven deepfakes and impersonation require integrating cybersecurity, physical security, HR and legal functions.

The opinion piece contends AI-powered impersonation, deepfakes and automated social engineering cross digital, physical and operational boundaries that siloed security programs cannot cover. It cites an EY survey of 250 corporate leaders where only 12% feel most prepared to detect a targeted physical attack, and describes transnational groups using deepfakes and stolen identities to bypass virtual HR hiring loops. The author urges unified cross-functional verification pipelines and shared threat intelligence between CISOs and chief security officers.

CSO Online · 1d agoIndustry

Revolut Data Breach Via Fake Government Requests – What We Know So Far

Revolut confirmed attackers extracted customer KYC records by sending fraudulent data requests from a spoofed or compromised government agency email domain.

Revolut confirmed a data breach in which an unauthorized party obtained sensitive customer records by submitting fraudulent information requests from an email account on a legitimate government agency domain with valid SPF/DKIM/DMARC authentication. Disclosed data could include full names, dates of birth, passport or driving-license copies, onboarding facial images, IBANs, account statements, withdrawal records, and complete transaction histories including Bitcoin activity. Crypto investigator ZachXBT assessed the operation targeted high-net-worth users, while a threat actor using the name 'IAmNotAVillain' claimed Italian law-enforcement departments were compromised over six months with 147 GB of material, claims that remain unverified. Revolut says only a limited number of customers were affected, blocked the email address, and notified regulators and affected customers, stating its systems and funds were not compromised.

Cyber Security News · 2d agoData breach

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent Space · 2d agoAI safety & security

Forgery of C2PA on a Pixel 10

Researcher forged a Google Pixel 10 C2PA content credential with genuine signatures, showing root-level attackers can fake photo provenance.

A Hacker Factor blog post demonstrates an AI-generated 'unicorn glitter milk' news photo carrying a valid, cryptographically signed C2PA manifest traceable to Google's Pixel camera certificate chain, passing validation in Adobe Inspect and the CAI Verify tool with a verified timestamp. The author, working with UMBC's PASAWG working group, reported to Google and C2PA in November 2025 that root access on a Pixel device could sign arbitrary images as camera captures; after 90 days without resolution, details were published. The finding undermines C2PA Assurance Level 2 claims made for Pixel 10 Content Credentials.

Lobsters · security · 19h agoResearch

Unsolved Problem by Fields Medalist Breached by Two High School Students

Two high school students used Claude Opus 5 and GPT-5.6 Sol to help solve an open Lorentzian polynomials problem, posting a 75-page arXiv proof.

Aayush Bathija and Prince Rohatgi of Oak Park High School, mentored by UCLA postdoc Daniel Soskin, published the 75-page paper 'Bounded Ratios for Lorentzian Polynomials' (arXiv 2609.05341), solving an open problem in Fields Medalist June Huh's Lorentzian polynomial theory. The main structural theorem extends bounded coefficient-ratio characterization from quadratic to arbitrary-degree polynomials via discrete convexity conditions. The students used Claude Opus 5 and GPT-5.6 Sol for exploration and proof ideas but independently verified all arguments; the result follows an open letter from 25 Fields Medalists voicing concerns about AI's impact on mathematical rigor.

Cognition launches new SWE-2 model, Rivaling Fable 5.1 and GPT-Astra

Cognition released SWE-2, a coding model post-trained from Kimi K3 that scores 50.0% on FrontierCode 1.1 Main, near Fable 5.1 at 64% lower cost.

Cognition introduced SWE-2, its most advanced coding model, post-trained from the 2.8T-parameter Kimi K3 base model. It achieves 50.0% on FrontierCode 1.1 Main, 73.0% on DeepSWE 1.1, and 92.8% on Terminal-Bench 2.1, beating Grok 4.6 and SWE-1.7 while matching Fable 5.1 and GPT-5.6 Sol at a fraction of the price. The company says it scaled reinforcement learning to the multi-trillion-parameter regime for the first time, using Pareto-informed cost penalties that train all reasoning-effort levels in a single run, tripled RL environments, and NVFP4/FP8 quantization-aware training. SWE-2 is available today in Devin Desktop and CLI, with rollout on Devin Web and Fusion.

Hacker News · AIupdated · 1h agofirst · 6d agoModel release 12 sourcesHN 58↑ · 15 comments1